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future of AI
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The Future of AI in the Business World

future of AI

When it comes to the implementation of Artificial Intelligence (AI) in an enterprise, the world is at a crossroads. Although the technology that allows computers to mimic human thinking has advanced steadily over the last half-century, the Future of AI looks particularly promising. The cost-effectiveness of deployment, convenient access to cloud computing, and realistic business use cases are all positioned to help AI make a major impact in the business world in the coming years.

 

With the future use cases for AI in the industry on the way, and the capital investments and speed of progress currently powering AI, one thing is for sure: To realize the benefits flowing to the business world, you’ll have to get your framework in place relatively soon. But how are you going to do it? Business intelligence (BI) tools can help with this. Businesses can plan for the future while still taking full advantage of today by laying the groundwork with this readily available, open, and inexpensive software. Businesses are starting to question if it makes sense to move through an expensive deployment that won’t produce meaningful results for two or three years after having unrealistic expectations for AI, which have yet to emerge. Instead, they should concentrate on implementing BI today to get some quick results, then layering AI on top of existing BI data to extract new insights and generate greater value as the technology advances.

 

So, how can BI apps assist in preparing the company for AI, and what potential use cases can be derived from the combination of AI and BI?

Future of AI and What BI Software Do for You?

Whichever side of the Artificial Intelligence and Business Intelligence discussion you are on, one aspect is certain: you’ll need data to support both. There is no intelligence in AI or BI without data to operate on. There will be nothing to analyse or to which a learning algorithm can be applied. When it comes to intelligence solutions, data is the cornerstone that must be laid.

 

Data has never been more accessible in today’s business world due to the wider acceptance of cloud computing and the Internet of Things. However, the massive amounts of data produced every day are posing a new challenge for businesses: What knowledge is crucial? What are the best practices for tagging, sorting, grouping, and analysing data? What concerns are answered by disparate data points? How can data collection through various touch points, from retail to supply chain to a factory, be seamlessly implemented?

Data Warehouse

This is where data warehousing comes in. Data warehouses are a way of optimizing data obtained from various touch points, like point-of-sale, CRM, inventory, and warehouse management systems), structuring it to obtain needed insights, and running research. Enterprise companies cannot thrive without efficient data warehousing; data silos consume capital and resources quickly, and any company still attempting to piece together “business intelligence” from numerous reports and fragmented data will quickly fall behind those with centralized data and reporting. The integrated data warehouse, on the other hand, isn’t just a set of relational databases thrown together; it’s based on modern data storage systems like Online Analytical Processing (or OLAP) cubes.

 

Cubes are multi-dimensional data sets designed for analytical processing applications like AI or BI. Cubes are superior to tables in that they can connect and sort data across several dimensions, enabling non-technical users to access a wider wide range of role-specific and highly contextual data points to discover new insights and make real-time adjustments to strategies and decisions. Most non-technical sales agents and buying associates will struggle to link several tables along with a standard report, but with Business Intelligence cubes, all they must do is drag and drop the metrics and dimensions that apply to their own customized dashboard.

 

So, how do you get the data? SQL is a language for manipulating and extracting data from cubes. SQL was created as a common language for interacting with databases, irrespective of the type of database being used, and is ultimately the tool for extracting, retrieving, deleting, modifying, and handling data in a table.

Other Methods to Address Data Demands: The Future of AI

Aside from data warehousing and OLAP cubes that provide the technological base, there are a few other components that can assist enterprise businesses in meeting their data needs:

Data Modelling

Data modelling is a technique for sorting out individual data sources within an organization and deciding how they should communicate to obtain the most useful business insights. Data Modelling can be done at the conceptual (high-level, linked to business objectives), logical (mapping to each business function), and physical (how the actual measurements, metrics, and structures are related inside a data cube).

Analytics and Reporting

The ability to capture, structure and store data is essential, but the ability to analyse and report on it is the ultimate objective. End users can find the valuable insights they need with little technological expertise due to business intelligence solutions that provide easy, open analytics and reporting functions. It also facilitates business processes in avoiding unnecessary data bottlenecks by providing them with immediate access to the data they need.

Data Visualization and Dashboards

Business intelligence relies heavily on analytics and reports, but you are not alone if you have ever spent hours sifting through a table of values trying to find out what the data means. Important insights are presented in vivid graphical representations that are much easier for the user to understand using data visualization tools. According to Aberdeen Group research, businesses that use data visualization software are 28% more likely to find accurate information than those that depend entirely on controlled reporting; the same research also found that 48 percent of business intelligence users at companies with visual data exploration will find the information they need without the assistance of IT personnel. Dashboards can quickly compile visualizations and reports into customized displays for each end-user or business activity, by providing individuals with immediate access to KPIs that help drive improved business results from the ground up.

 

Protection, usability, and efficiency are three major benefits that business intelligence solutions help to drive, as well as three key indicators of enterprise business performance. Protection, usability, and efficiency are three major benefits that business intelligence solutions help to drive, as well as three key indicators of enterprise business success.

The Future of AI

Soon, AI algorithms will be expected to be efficiently implemented in your current data stores, providing you with even more insight. AI applications in line with business should fall into three categories:

Automated Processes

The most common use of AI in business right now is to automate systems and business processes. Although previous iterations of automation focused on sharing data between systems, AI can take this skill to the next level by interacting with data as if it were a person, either inputting or consuming as required. AI robots are now capable of analyzing legal contracts and extracting specific clauses, updating customer records through several networks, and automating customer outreach in response to changing

circumstances. Businesses will be able to automate even more processes as these algorithms become smarter.

Meaningful Insight

Cognitive insight is the ability to derive meaning and distinguish patterns from large amounts of data using AI algorithms. Although BI software and data stores will certainly include the “diet” for cognitive insight algorithms, as they learn, they will be ready to access those learnings to larger data sets, respond to new data in real-time, and recognize possible data matches across multiple platforms.

circumstances. Businesses will be able to automate even more processes as these algorithms become smarter.

Cognitive Engagement

The human-interfacing aspect of AI is referred to as cognitive interaction. Consider chat-bots, knowledge bases, and product recommendation engines, among other things. Externally (for customers) or internally (for employees), cognitive engagement technologies can be used to simplify the connection between users and systems. Since companies are still wary of the relatively new technologies, most existing applications concentrate mainly on internal engagement. However, as AI growth and implementations progress, objections are likely to fade away as companies discover new ways to use existing data to drive practical automated interactions with humans all over the world.

circumstances. Businesses will be able to automate even more processes as these algorithms become smarter.

Takeaway

The future of AI will eventually start to live up to its potential. We have been reading a lot about the excitement in the business world. Computers can assist in ushering in a new age. For cutting-edge businesses, a new age of growth and profitability awaits, but only if you have already laid the groundwork, which begins with business intelligence.

 

At Global Data 365, we understand that business intelligence and data management are essential components of every enterprise artificial intelligence strategy. To get the most out of artificial intelligence, you need to start with good reporting and analytics. So make sure you are laying the groundwork for your company’s future success today!

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Overcome Your Fear of Advanced Analytics
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Overcome Your Fear of Advanced Analytics

Overcome Your Fear of Advanced Analytics

We have all read that information is nothing unless it can be turned into meaningful data. It can be daunting in business to have access to so much data. How do you know where to begin when you’re bombarded with information It’s possible to get lost during it all, overwhelmed by the flood of data and uncertain where to start looking for ways to improve business processes. That is where you can utilize advanced analytics. 

Advanced analytics is the automated or semi-autonomous analysis of data using materials and tools that go beyond traditional business intelligence (BI). It’s a catch-all word for several analytics sub-fields that collaborate using predictive capabilities. High-level approaches and software forecast future patterns, activities, and events, allowing businesses to create “what-if” models and estimates to future-proof their operations. 

Advanced analytics involves data mining, big data, and predictive data analytics, which allows you to mine your data for deeper, more analytical, and eventually actionable insights. Whereas traditional analytical methods show you where you’ve been, advanced analytics focuses on where you’re going next, providing insight into what could happen based on a variety of potential opportunity scenarios. 

Advanced analytics includes newer technology such as machine learning and artificial intelligence, and visualizations. Advanced analytics encompasses so many areas and has such a wide range of applications that it has a variety of applications, including marketing, inventory and warehousing, and manufacturing. Keeping this in mind, it appears that any company should be interested in using advanced analytics to solve critical business problems. 

Listed below are the five main strategies for increasing profit in 2021 using your ERP system and comprehensive financial reporting tools. 

Assumptions Regarding Advanced Analytics

Many CFOs still have assumptions about advanced analytics: 

 

– They cost money. 
– They take time to deploy. 
– They are complex to understand. 

Advanced Analytics is Costly

You might be wasting money if you’re sitting on a heap of useful data and aren’t analyzing it because you’re afraid of investing in advanced analytic tools. Your data is your most valuable resource for uncovering answers to your potential questions by properly processing your history. 

 

Many Enterprises Resource Planning (ERP) systems quickly integrate with external services that are both dependable and cost-effective. When you are likely to afford less time doing the hard work and more time understanding the report findings, the rewards can quickly outweigh the costs. 

Deployment takes Time

Yes, some technology takes a long time to get up and running. Running out the first ERP or switching to a new one is a lengthy process that can take months to complete, and that’s assuming everything goes smoothly. 

 

This is not the case for advanced analytics. Many of these systems can be set up in a matter of hours, if not minutes, and begin crunching the data right away. 

Complex to Understand

Although advanced analytics was developed to use complex formulas and equations, they are used to provide the end-user with data that is simple to understand. In reality, several advanced analytics user interfaces are built to help people from all walks of life use data to search for information. 

 

Enterprise solutions can also assist users in learning techniques by assisting them in selecting and processing appropriate data from a variety of sources. The end-user’s experience will be simple to navigate, regardless of the technicality of what advanced analytics might be doing in the context. 

 

This allows sellers more versatility and, in certain cases, provides new business possibilities (via Amazon or eBay, for example), but that also makes it more difficult to get a clear picture of product revenue across platforms. When businesses use the automated reporting tools offered by each e-commerce platform provider, they get a much-distorted vision of their online business. Business executives will obtain consistent visibility into all their sales operations, through all sales channels, including e-commerce, by putting data together under one platform and then validating it so that it offers an apples-to-apples comparison. 

Still Having Doubts?

If you’re still having doubts about using advanced analytics even after clearing out the assumptions, we are here to clear them out. 

 

Begin by gathering the information you’ll need to examine. For your business, this may have been a time-consuming process in the past. Data is stored in an ERP (or two) as well as other diverse relational databases that don’t always get along. As a result, putting together the data could have required many data backups and several hours of manipulation to get it into the format you need. If the data changes during this phase, for example, if you receive a late invoice payment that still counts against the month you’re working on, you’ll have to restart the whole process. 

 

Using Global Data 365’s finest reporting systems, you can connect data from more than 140 ERPs and EPMs, as well as other relational databases, into one automatic report that lives inside the framework of Excel or displays in a readily available web-based dashboard. Dynamic links are used in our solutions to extract real-time data from your ERP, connect it to other sets of data, and deliver the accurate reports you require based on safe and simple-to-assemble parameters. 

 

With one click, you can check your reports. Return information for a single account, a collection, or a wildcard quest. It’s all designed to offer users quick and easy access to their data so they can spend less time figuring out what is going on and more time predicting the future. 

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9 Ways you are failing at Business Intelligence
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9 Ways you are failing at Business Intelligence

9 Ways you are failing at Business Intelligence

Business intelligence is critical for making strategic business decisions, but often organizations’ BI efforts are hindered by bad data practices, tactical errors, and other factors. Executives understand the importance of having high-quality data when making business decisions. However, obtaining reliable data in a timely and user-friendly format continues to be difficult. Yes, there is a struggling market for business intelligence (BI) analysts and distributors. How can you determine 9 ways you are failing at Business Intelligence and it’s time to update or recruit specialist experts? Knowing where others have gone wrong will help you answer these questions. 

Doing What Customers Ask, Instead of What a Company Needs

Surely placing customer satisfaction as the top priority leads a company to success. However, when it comes to technology, business users can not always grasp what they are requesting. Apart from that, they try to impose the solution’s technical information. 

 

BI failure is a result of implementing what consumers want rather than what they need. Successful BI projects necessitate the ability to adequately verify BI findings, and the ability to elaborate and manage requirements. One way of understanding what consumers really need is to use the “5 whys” approach, which involves asking why five times about a single problem to gain greater depth.  

Using Less Time and Money for Testing

In the marketing world, thinking about moving fast and breaking things is a common mantra. And well-established companies need pace. However, in the race to go faster, things that are seen as additional services, such as testing, will suffer. Seeing testing as a waste of time may lead to serious quality problems, particularly if manual testing is used. Instead, look to research and related “ancillary” processes to provide a better BI experience. 

Limiting testing, particularly when the only testing performed is manual, results in a high number of errors in user testing, which has an impact on product delivery. 

Short-Term Broader Data Integrity is Important

Reading, viewing, and analysing data is convenient with business intelligence software. But what if the data you’re providing the system is tainted? Or, to put it this way, how can you show an IT analyst that your management decisions are based on high-quality data? If you concentrate solely on the BI tool and its setup, you can overlook this crucial information. 

Taking a Defensive Approach to Unsatisfied Customers

Dealing with irritated users is not something any technology expert looks forward to. There will be system errors and annoying points. Your response to these issues will determine if your BI project succeeds. 

 

The two most common mistakes that BI newcomers make are concentrating all their attention on delivering requests and failing to include business end-users in the project. What matters is, are you providing your customers with the information they require to make decisions? Do you know what information they require? Is there an alternative to making a new report to solve the problem? It’s preferable to prioritize user complaints based on their relative relevance to your overall plan rather than simply dismissing them. 

Conducting Analysis with No Purpose

When you have effective resources at your side, it’s only normal to look for ways to use them. Business intelligence without guidance, on the other hand, is a waste of time. This issue is especially prevalent among young professionals. 

 

Inexperienced and eager business intelligence practitioners risk developing tunnel vision and doing interesting research that isn’t motivated by meaningful questions. The findings often lack a ‘so what’ finding and struggle to offer actionable insights. It takes business knowledge and judgement to avoid this blunder. One way to avoid the “so what” dilemma is to ask yourself, “How does this research apply to the company’s goals?” 

Thinking Data is Sufficient

Is it possible that “more data” can solve all our business problems? Many aspects of business intelligence and analytics are based on this unspoken presumption. It’s not going to be working to just drop data at an executive and hope for the best. 

 

Data is dismissed or trumped by belief if it isn’t interpreted and argued convincingly. The importance of making a strong case and crafting a compelling narrative can never be underestimated. The field analysts may be aware of the implications of data collection. You can’t presume that those who are a few steps away from the data will understand that argument. 

Relying only on BI tools

Technologists understand that the right method will make a huge difference. Consider the first time you used a script to automate a time-consuming process. Those early victories motivate you to keep looking for new ways to solve business problems. Unfortunately, putting too much reliance on your business intelligence tool can lead to disappointing results. 

 

Even if the tools are becoming more user-friendly, there are process, cultural, and learning elements that must be addressed to achieve progress. 

Vendor Management is Ineffective

It is possible that your organization doesn’t have a business intelligence department. Working with outside experts makes sense in that situation. You could hire them to act as an outsourced service provider or to help on a particular project. In any case, you must know your vendor and provide oversight, particularly when it comes to subcontractors. 

 

It is your duty to manage the problem and figure out who is working on your behalf if a third party is involved. Otherwise, you might be in for a BI failure. 

Dismissing Tools like SQL and Excel

Are you aware that there are Microsoft Excel championships held every year? Take, for example, the Microsoft Office Specialist World Championship, which attracts over 500 thousand participants and offers cash prizes to the winners. That is just one indication of Excel’s growing popularity in the corporate world. SQL has a large following in the technology community but to a lesser extent. 

Identify these 9 ways you are failing at Business Intelligence and make a big shift with power of BI in a company with ramifications for employees’ jobs. In leading people through the process, the practice of change management and leadership cannot be overlooked. 

If you’re interested in knowing how agile BI solutions can lead your company to success, contact us now, to eliminate these 9 ways you are failing at business intelligence and lead your way to data driven insights.

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Power BI with Jet Analytics
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Power BI with Jet Analytics

Power BI with Jet Analytics

Business intelligence is a much better and less expensive choice than data warehousing for 90% of small to mid-size businesses. Both systems used together; Power BI with Jet Analytics have the same overall goal: to improve data analysis. The immense effort and cost needed to define the data tables and relationships required to drive analytics put data warehousing out of reach for most businesses. Due to the extreme minimal effort and expense needed to get it up and running, business intelligence is becoming the choice of small to mid-size companies, irrespective of which of the two most popular options are used.

 

Jet Analytics from insightsoftware (previously Jet Global) and Power BI from Microsoft are the two most popular business intelligence options in the Microsoft Dynamics environment. Jet Analytics can use either Excel or Jet Reports as a reporting tool, allowing you to have the best experience. Jet Analytics uses pre-defined data cubes to describe the patterns in the data necessary for reporting. Because the table relationships required for accounting, which are focused on financial processes, are not always the same as those required for business analysis, which could be more operational, this method works. This method has many disadvantages, including a higher initial cost, more work to create new data relationships into the data cubes, and the fact that data is only as current as of the last update.

 

A major benefit is the simplicity with which new reports can be created if they match the data cubes, as well as the improved accuracy since the reports are run against a replica of the output database rather than the live database itself. Data can be processed into data cubes from various sources, not all accounting systems.

Benefits of Using Power BI with Jet

Power BI depends on one or more databases to provide real-time or near-real-time data. This means that data is updated in real-time, but output for more detailed reports will not be optimal. Almost any form of the report can be created and distributed through the web or mobile devices. Every consumer can create their own dashboards, each with its own unique insight. It is possible to set up alerts. The details behind the reports can be drilled down by users. To use Power BI, you will need an Office 365 subscription.

 

You cannot really go wrong anyway. Invest a little more upfront to identify data relationships using data cubes in Jet Analytics or subscribe to Office 365 and use Microsoft BI Power to provide your users real-time access to important analytical data. To explore more about these better, less expensive alternatives for your company, we offer 30 days free trial license for you to test it on your very own database or get a personalized training for yourself.

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Optimize Processes with Data Visualization
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Optimize Processes with Data Visualization

Optimize Processes with Data Visualization

Every aspect of a company relies on making prompt, well-informed decisions. Data is at the center of the financial services sector. Traditional business intelligence (BI) methods aren’t up to the task with so much data to rummage through. These techniques were designed for tabular reporting and can only handle small volumes of homogeneous data; they also require advanced technical expertise. Today’s software can process and interpret massive amounts of data in real-time, with a level of elegance previously unseen. By leveraging modern tools to optimize processes with data visualization, companies can transform complex datasets into actionable insights, enhancing decision-making efficiency across all departments. According to a report conducted by Gartner on the top priorities of CFOs, here’s what they looked at: 

– Enhancing Financial Analytics: 
Even after a 50% rise in financial analytics expenditure in the last three years, only a few businesses have advanced analytics capabilities. As analytics becomes a central responsibility of the finance department, this must change. 

 

– Reorganizing Finance Teams: 
Traditional approaches for coordinating and using finance teams are becoming less effective as the popularity of finance teams grows. To stay relevant, the department needs a shakeup from the top down. 

 

– Finance Technology Optimization: 
Finance teams must maximize the value of their ERP systems while also adopting newer innovations and planning to become more tech-savvy. If this isn’t done, the finance department will become less intelligent and agile. 

 

Any of those projects could keep a CFO busy for a year without yielding much progress. However, if such executives consider these problems analytically, realizing how the challenges and goals intersect, a surprising approach emerges, data visualization. 

Data Visualizations

There has almost certainly been some kind of data visualization for as long as there has been data. Charts and graphs have recently become commonplace in business due to Excel spreadsheets. Users soon realized that visual interfaces help them understand complex information. Instead of manually examining a spreadsheet, they could quickly recognize the key takeaways by looking at a pie chart. Digital visualizations provided the finance team with a unique outlook on data and a game-changing method for decision-making, compared to what was previously available. 

 

Today, visualizations have taken yet another step forward, possibly the most important yet. Advanced visualization features are included in today’s top financial reporting tools, which run on top of ERP and beyond the constraints of Excel. Such visualization tools do more than improve on what has come before; they turn the relationship between the finance team and the data on which it relies more highly than it has ever been. 

Advances in Data Visualizations

So, what’s the difference? To begin with, visualizations have progressed well beyond basic graphs and maps. They can now visualize data in new systems that provide more context and information. Users can view the optimal visualization to encompass the data rather than trying to settle for a sufficient option with this enlarged toolkit at their disposal. 

 

After you have made that decision, creating the visualization is nearly seamless. It only takes some clicks to move data from one area to another in several cases, rather than a lengthy manual process. This not only saves time and eliminates mistakes, but it also helps everyone inside or outside the finance department to create their own visualization without any need for advanced training. 

 

Lastly, and perhaps most critically, visualizations have moved to the foreground of decision-making. The finance members can quickly integrate them into financial reports and structure them to optimize the insights they contain as well as the ease with which they can be extracted. The design features within such reports are also not static. They update themselves as new information becomes available, making them more like interactive indicators that monitor key metrics in real-time than visualizations.

 

In addition to finance, operational and supply chain management teams benefit from these dynamic features. Inventory dashboards, for example, provide real-time insights into stock levels, supplier performance, and demand forecasting. This allows organizations to streamline their operations, reduce costs, and make informed decisions across departments. Integrating financial reports with operational data ensures a comprehensive view of business health, enhancing decision-making at both the strategic and operational levels.. 

 

Everything in today’s visualizations is vastly superior to previous versions. Despite this, it’s always easy to underestimate their effect on the economy. The CFO, the finance team, and the company are all involved. 

Using Data Visualizations to Optimize Processes

Data visualizations not only help people view data in new ways, but they also help them see it more clearly, presenting insights, opportunities, and challenges that would otherwise go unnoticed. 

 

One form of data visualization does this is by compressing large volumes of data into a readily available layout. Financial reports influence decision-making, but in the past, they were either too simple to show anything of value or too difficult to stir up an action. Today’s visualizations bridge the gap, allowing reports to include what decision-makers need to know while still revealing those insights in real-time. 

 

Advanced data visualizations also allow F&a to investigate financial data on their own terms. Decision-makers know what knowledge they want better than everyone else, and once it’s simple to find it and visualize it as needed, understanding differences disappear. To look at it another way, visualizations open a vast array of nuanced financial data to the point that it can be explored. Anyone interested in delving deeper into the data now has a great starting point. 

 

Visualizations help practitioners outside finance grasp a topic that can be perplexing to the general reader, in addition to CFOs. Executives and heads of departments need to consider how their decisions impact the company’s finances on a micro and macro level, but many lack the knowledge to do so from a dense spreadsheet presenting a financial report. However, when presented with visualizations, the material emerges in a manner that everyone can comprehend. As a result, financial knowledge grows across the board, helping companies optimize processes with data visualization for better decision-making.

Data Visualizations: a Modern Solution

Finance teams will use innovative data visualizations to make significant progress on every one of 2021’s top priorities. Once implemented, analytics improve dramatically, accountants spend less time manually processing data, and the ERP ceases to be a barrier to understanding. 

 

Global Data 365 offers visualization tools to optimize finance processes. In terms of usability, precision, and variety, these resources far exceed what you’ve come to expect from Excel. Even better, they’re just one of many features available in purpose-built financial reporting tools that are designed to work with today’s most common ERPs. 

 

If you’re searching for a new perspective on data, we offer a comprehensive upgrade. To see how this all operates, request a free demo today. 

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Cash Flow Analysis with Microsoft BI
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Cash Flow Analysis with Microsoft BI

Cash Flow Analysis with Microsoft BI

With the advancement in technology, it is more important than ever to understand how cash flow analysis will affect your company and how technology, such as business intelligence (BI), can help you keep track of your cash. 

What is Cash Flow Analysis?

Financial reporting requires the use of cash flow analysis. You can tell where cash is produced and invested by looking at your company’s cash inflows and outflows over time so you can prepare accordingly. Controlling your cash will help your company not only stay afloat through difficult times but also open gates to new opportunities. 

 

Have you had a profit or a loss? Cash flow is important at any point of a company’s development cycle, whether you’re a new start-up or an existing company. Anything you do requires money, from managing assets to hiring a new employee. To achieve security and consistency, you must have the right tools and structures in place at the right time to help you manage and predict your cash flow. 

Different Approaches to Cash Flow Analysis

At the end of each quarter, most accounting teams are responsible for conducting a cash flow analysis to determine that all the company’s expenses are taken into account. 

 

Free Cash Flow (FCF) is among the most valuable financial performance indicators. Experts look at FCF or operating cash flow minus capital expenditures to determine how much money a business has left over to broaden or return to shareholders. You have an issue if your expenditure exceeds your income. 

 

A cash flow statement is a crucial tool for managing cash flow, and it contains data from operations, investing, and financing. A cash flow statement is traditionally created to use Excel-based manual data analysis. It can be difficult to combine data from your cash flow analysis, expected and real operating expenses, capital expenditures, accounts receivable/payable balances, and general ledger data. Excel costs time and money. Identifying the ramifications, many businesses have simplified manual accounting processes and adopted business management and intelligence technologies to better analyze and predict cash flow. 

Cash Flow Analysis with BI

Companies have embraced business intelligence technology to change the way they handle their cash flow now that the platform is more available and affordable. Companies use business intelligence and analytics software to automate cash flow analysis and provide the tools they need to analyze data optimize cash flow analysis, and more. 

 

Review the Jet Sample: Cash Flow Statement.

 

The best feature of business intelligence software is that it is designed to provide more precise financial statistics and, as a result, eliminate the guesswork from the cash flow analysis process. BI solutions provide managers with reports that are timely, reliable, and simple to use. 

 

Here are a few examples of how BI is assisting companies all over the world in better managing their cash inflows and outflows. 

- Intelligent Predictions

Financial predictions enable you to prepare for the allocation of resources and budgeting by providing a clear way to make strategic business decisions. Cash predictions can be generated automatically using BI software. Financial managers can remain updated with this ability, including advanced warnings of cash shortages or surpluses. This enables a business to respond rapidly to growth potential or to cut back when necessary. 

- Data Management

Assembling data from various sources is the most time-consuming aspect of cash flow analysis by spreadsheet. You will get the figures you require in real-time using BI software that combines with your ERP and CRM solution. The cash flow analysis will provide more useful insights and up-to-date reports, allowing you to make fast, data-driven decisions. 

- Manage Projects

Large projects may have a significant impact on cash flow. For cash flow development and proper development, financial managers need greater control of what goes in and what comes out, so the ability to analyse a project’s length, expenses, resources needed, and payment terms is critical. 

- Plan Inventory

There are some costs involved with the inventory. It not only binds up cash in goods but getting too much inventory can also be harmful to your cash flow. You will make a decent source of supply and be more careful with inventory spending with BI tools. In the long run, BI will save you a lot of time and money by sales forecasting and intelligent reporting. 

- Risk Management

Should you put money into a new venture? Should you temporarily reduce your spending? Risk management software such as BI software is a reliable tool. If you have a cash flow problem, if your prediction indicates that you may not have enough cash, a BI solution will enable you to perform a fast prediction and liquidity analysis to assist you in making the best decision possible. 

BI Solution

BI tools help data-driven analysis and decision-making, which is just what you need to keep a tight grip on your cash flow. Although there are many BI solutions available today, particularly for Microsoft Dynamics users, there is no such thing as a “one-size-fits-all” solution. 

 

We are here to assist you if you want to improve your financial statements and cash flow review. Contact us today! 

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How Does Business Intelligence Help in Demand Forecasting
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Business Intelligence Help in Demand Forecasting

How Does Business Intelligence Help in Demand Forecasting

Businesses are investing significantly in advanced analytics to maintain a competitive advantage and improve their result due to big developments in artificial intelligence and machine learning. Business Intelligence in Demand Forecasting is one of these fields where businesses extract information from existing data to assess purchasing patterns and predict future trends through predictive analytics.

 

Predictive analytics makes use of a combination of data, statistical algorithms, and machine learning approaches to predict the likelihood of future outcomes based on the past. Every sector, from banking to retail, uses this technology to assess consumer responses or orders, forecast inventory, manage capital, and even detect fraud. Predictive analytics is becoming more popular, even though it has been around for decades, thanks to increasing quantities of data and readily available tools ready for a transformation. 

 

Below we will look at how market intelligence can help with demand forecasting, a type of predictive analytics that focuses on consumer demand. We’ll go into what demand forecasting is, how it operates, and how to get started with it using business intelligence tools. 

What is Demand Forecasting?

Demand forecasting is a type of predictive analytics that focuses on predicting customer demand for products and services. It estimates potential demand based on historical data and current market conditions and sets the level of supply-side preparedness needed to match demand. 

 

Demand forecasting is important in production planning and supply chain management, even if it isn’t an acquired skill. Demand forecasting impacts everything from budgeting and financial planning to capacity planning, sales and marketing planning, and capital investment. 

Why Should You Use Demand Forecasting?

Manufacturers, distributors, and retailers use demand forecasting as an important part of supply chain planning to gain insight into their activities and make educated, efficient decisions about pricing, inventory stock, resource optimization, and more. 

Listed below are some major reasons why demand forecasting is so important in today’s supply chain: 

 

  • Increased customer loyalty (providing customers with the items they want, whenever they want it). 
  • Inventory management to minimize stock-outs and overstocking. 
  • Effective raw material and labor scheduling. 
  • Improved capacity planning and resource allocation. 
  • Better distribution planning and logistics. 
  • Affordable pricing and promotion. 

Use of Business Intelligence in Demand Forecasting

Data is used in demand forecasting. If the data you use is incorrect, the math and how you apply it will result in under or overestimated demand, leaving you with a slew of disgruntled customers or an overabundance of goods. Most businesses use a business intelligence solution to help with data planning, data co-ordination, and forecasting to better understand demand and supply. 

 

Business intelligence software is designed to capture, unify, sort, tag, analyze, and report on large volumes of data. Here are four main areas where market intelligence can help you get started with reliable demand forecasting: 

Data Preparation

Most businesses fail to cleanse, verify, and audit their data regularly. As a result, 40% of company data is either incorrect, incomplete, or inaccessible (Gartner). BI software allows you to organize and monitor your data in one place, ensuring that your analytics are based on reliable data. 

Data Collection

A data warehouse can assist you in gathering business data from a variety of sources and using it for accurate reporting and analytics. Data warehouse-powered BI will help correlate data from different systems to provide further visibility into the supply chain, revenues, and financials, among other items. 

Data Analysis

BI software is built for processing and measuring large quantities of data. Maintaining a system of records, which includes historical records and various data sources, ensures that all findings are based on the same version of the facts. 

Reporting and Analytics

With pre-built dashboards, BI software will give you a single view of results and reports for the rapid dissemination and exchange of real-time information on demand. This encourages better preparation and coordination between the teams. 

 

Improve your data quality and plan your data for reliable demand forecasting by learning more about what you need to do. At Global Data 365, we will analyze your current systems and show you how business intelligence will help you build the technology base for your company. 

 

Contact our team for more information! 

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What are Data Lakes?
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What are Data Lakes?

What are Data Lakes?

The huge volume of data collected by today’s company has entailed a drastic change in how that data is stored. Data stores have expanded in size and complexity to keep up with the companies they represent, and data processing now needs to stay competitive, from simple databases to data warehouses to data lakes. As enterprise businesses collect vast amounts of data from every imaginable input through every conceivable business feature, what started as a data stream has developed into a data flow.

 

A new storage solution has emerged to resolve the influx of data and the demands of enterprise businesses to store, sort, and analyze the data with the data lake.

What are Data Lakes?

Data Lakes are type of centralized repository that stores all types of data—structured, semi-structured, and unstructured—in its raw format. Unlike data warehouses, which standardize data before processing, a data lake holds data without any transformation, allowing for future analysis and exploration. This raw data can later be structured for specific purposes, making it a powerful resource for businesses that deal with diverse data sources like IoT devices or event tracking.

What Does It Contain?

The foundation of enterprise businesses is a collection of tools and functions that provide useful data but seldom in a structured format. The company’s accounting department may use their chosen billing and invoicing software, but your warehouse uses a different inventory management system. Meanwhile, the marketing team is dependent on the most efficient marketing automation or CRM tools. These systems rarely interact directly with one another, and while they can be pieced together to respond to business processes or interfaces through integrations, the data generated has no standard performance.

 

Data warehouses are good at standardizing data from different sources so that it can be processed. In reality, by the time data is loaded into a data centre, a decision has already been taken about how the data will be used and how it will be processed. Data lakes, on the other hand, are a larger, more unmanageable system, holding all of the structured, semi-structured, and unstructured data that an enterprise company has access to in its raw format for further discovery and querying. All data sources in your company are pathways to your data lake, which will capture all of your data regardless of shape, purpose, scale, or speed. This is especially useful when capturing event tracking or IoT data, while data lakes can be used in a variety of scenarios.

Benefits of Data Lakes

  • Versatility: Data lakes store data in any form—whether it’s CRM data from marketing or raw transaction logs from inventory systems.
  • Flexibility: Since data is stored in its original format, it can be processed, transformed, and analyzed whenever needed.
  • Scalability: Data lakes, like Azure Data Lake, handle data of any volume, shape, or speed, making them ideal for large-scale enterprises.

Application of Data Lakes

Data lakes find applications across multiple industries, enabling:

  • Healthcare: Early disease detection and personalized treatments.
  • Finance: Fraud detection and market trend prediction.
  • Retail: Customer behavior analysis and inventory optimization.
  • Manufacturing: Predictive maintenance and production workflow enhancements.

Data Collection in Data Lakes

Companies can search and analyse information gathered in the lake, and also use it as a data source for their data warehouse, after the data has been collected.

 

Azure Data Lake, for instance, provides all of the features needed to allow developers, data scientists, and analysts to store data of any scale, shape, or speed, as well as perform all kinds of processes and analytics across platforms and languages. Azure Data Lake simplifies data management and governance by eliminating the complications of consuming and storing all of your data and making it easier to get up to speed with the queue, streaming, and interactive analytics. It also integrates with existing IT investments for identity, management, and security.

 

That being said, storage is just one aspect of a data lake; the ability to analyse structured, unstructured, relational, and non-relational data to find areas of potential or interest is another. The HDInsight analytics service or Azure’s analytics job service can be used to analyse data lake contents.

Data Collection and Analysis

Data lakes are especially useful in analytical environments when you don’t understand what you don’t know with unfiltered access to raw, pre-transformed data, machine learning algorithms, data scientists, and analysts can process petabytes of data for a variety of workloads like querying, ETL, analytics, machine learning, machine translation, image processing, and sentiment analysis. Additionally, businesses can use Azure’s built-in U-SQL library to write the code once and have it automatically executed in parallel for the scale they require, whether in.NET languages, R or Python.

Microsoft HDInsight

The open-source Hadoop platform continues to be one of the most common options for Big Data analysis. Open-source frameworks such as Hadoop, Spark, Hive, LLAP, Kafka, Storm, HBase, Microsoft ML Server, and more can be applied to your data lakes through pre-configured clusters tailored for various big data scenarios with the Microsoft HDInsight platform.

Learn More About Microsoft HDInsight

Future-Proof Data

For companies, data lakes reflect a new frontier. Incredible possibilities, perspectives, and optimizations can be uncovered by evaluating the entire amount of information available to an organization in its raw, unfiltered state without expectation. Businesses may be susceptible to data reliability (and organizational confidence in that data) and also protection, regulatory, and compliance risks if their data is ungoverned or uncatalogued. In the worst-case scenario, data lakes will have a large amount of data that is difficult to analyse meaningfully due to inaccurate metadata or cataloguing.

 

For companies to really profit from data lakes, they will need a clear internal governance framework in place, as well as a data catalogue (like Azure Data Catalogue). The labelling framework in a data catalogue aids in the unification of data by creating and implementing a shared language that includes data and data sets, glossaries, descriptions, reports, metrics, dashboards, algorithms, and models.

Built your BI Infrastructure

The data lake will remain a crystal-clear source of information for your company for several years if you set it up with additional tools that allow for better organization and analysis, such as Jet Analytics.

 

At  Global Data 365, you can contact our team to find out more information on how to effectively organize your data or executing big data systems seamlessly.

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Budgeting Problems That Companies Face in Fiscal Planning
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Budgeting Problems That Companies Face in Fiscal Planning

Budgeting Problems That Companies Face in Fiscal Planning

Organizations all over the world are putting in more effort than ever before to achieve long-term, successful growth. Fiscal planning, which includes compiling, tracking, and reviewing a company’s income, expenditures, debt, and capital estimates for implementation in the annual budget, is a result of that growth strategy. It’s a big organizational challenge that happens once a year but typically lasts longer than expected. 

 

If you ask every big company’s CFO, they will tell you that during this time of organizing staff, aligning numbers, and handling approvals, they’ve probably missed a few nights (or weeks) of sleep. They are the ones that are largely responsible for determining priorities, benchmarking business results, making changes, and implementing the budget company-wide, even though there are several different participants in the budgeting process leading to budgeting problems. It goes without saying that without the correct structures and processes in place, this can be a challenging time. 

Budgeting and Fiscal Planning

Budgeting is necessary to direct daily revenue and expenditure decisions and assign resources. Long-term fiscal planning needs resources and support for financial targets. Although budgeting is intended to keep the business on track and find areas for change, the fact is that it is not a simple job. Rather than focusing on profitability and competitiveness, the budgeting process is often time-consuming and labor-intensive, with little return on investment. Tackling down the root issues, we conducted research and listed the top eight budgeting issues that most businesses face while preparing their fiscal year. 

Time

Coordinating, editing, and consolidating various budget contributors’ versions of the same static spreadsheet takes a long time. Many CFOs have reported spending upwards of 250 hours on the budgeting process itself, from time spent reinforcing numbers to missed hours spent tracking down individual budget participants. 

Communication

Before, during, and after the budgeting phase, there seem to be a lot of moving parts in a business. Budget developers, contributors, and approvers must all provide feedback at each point, but many businesses lack a tool to facilitate collaboration. They end up budgeting in silos, with no collaboration with other departments or a clear end goal in sight. 

Complexity

Trying to deal with deadlines and unanticipated adjustments is another issue that many budget owners face throughout the multi-layered budgeting process. Any change or alteration to a budget result in a complex back and forth hassle of redoing numbers, responding to questions, and re-sending spreadsheets, which should be an easy fix. 

Flexibility

When developing a budgeting document for all managers in an organization, it’s crucial that the form or spreadsheet they must fill out be structured and simple to comprehend. The problem is that unregulated spreadsheets lack the structure and marking needed for all budget participants. As a result, many people become engrossed in the information and find it difficult to provide correct answers. 

Accuracy

Most businesses end up depending on manual data entry and procedures to put together 30 to 100 Excel files (each with different versions). Manual processes are notorious for causing human error, inconsistencies, and a lack of control since there is no easy way to filter down the numbers. 

Optimization

Monitoring and changing the budget during the year is an effective business practice that contributes to increased profits and productivity. But, due to technical limitations and the manual labor needed to combine actuals and budgets, many businesses do not use it. 

Cost

The cumulative cost of several annual budgeting projects will stack up once all the time and money that the six budgeting issues above consume are added together. Aside from the labour costs associated with inefficient procedures, many businesses are unaware of the value that good budgeting and fiscal planning can bring to the table. 

Value

Perceived importance is one of the most critical factors in the budgeting process. Is the money you spend on planning and budgeting worth it? Operating managers should be able to make informed choices that are in line with the company’s overall financial priorities thanks to fiscal planning. 

Key Takeaways for Fiscal Planning

At Global Data 365, we have learned these budgeting problems from our monitoring and analytics customers time and time again. As a result, with our new budgeting tools, we want to improve the way you budget. Our budgeting system is a simple, adaptable, and simple-to-use fiscal planning solution that manages and streamlines the budgeting process in Excel and on the web from more than 140 ERPs. Users can use their existing Excel skills to transform the budgeting process into an easily controlled, systematic process that can be completed in half the time with traditional Excel integration and an interactive web portal. 

 

Here’s how we can help you gain more control over your processes and make your next budgeting period easier: 

 

– By eliminating manual processes and disparate structures, you can save time and money on financial planning. 

 

– Easily create, compile, and report on the budgets on a single forum for budget owners and contributors. 

 

– With planned, automated workflows, you can cut the budget timeline in half. 

 

– For simplified budget and actual reporting, import data directly from over 140 ERPs. 

 

– Improve financial efficiency across departments by increasing productivity with fast, reliable budget numbers. 

 

Budgeting tool that is both affordable and versatile, and that works the way people want a financial planning tool to work. Businesses can reduce the budgeting process, produce more reliable numbers, increase financial results and efficiency, and make better decisions in half the time. 

 

If you’d like to gain control over your budgeting problems, schedule a demo with us today! 

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Migrating from On-Premise ERP to Microsoft Dynamics 365 F&SCM
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Migrating from On-Premise ERP to Microsoft Dynamics 365

Migrating from On-Premise ERP to Microsoft Dynamics 365 F&SCM

Importance of Reporting Tools in Business Management

Many software companies are adopting a cloud-first strategy for designing, deploying, and selling their products. ERP is no different. Microsoft has been improving its range of ERP and CRM business applications to suit a cloud-centered strategy for many years. Customers of Microsoft Dynamics AX, Microsoft Dynamics NAV, Microsoft Dynamics GP, and Microsoft Dynamics SL will eventually move to one of the two cloud-based ERP products, Microsoft Dynamics 365 Business Central (D365 BC) or Microsoft Dynamics 365 Finance & Operations (D365 F&O).

 

Microsoft will target its resources in the future on only those two ERP products. Microsoft D365 F&O is aimed at mid-sized companies, while Microsoft D365 BC is more suited to smaller businesses with simpler needs. Both technologies have their origins in one of Microsoft’s current ERP code lines (AX and NAV, respectively), but the company has redesigned its technology and made major improvements. Microsoft is likely urging you to consider moving to the cloud if your company is currently using any of the Microsoft Dynamics legacy products. Microsoft continues to support its legacy products until at least 2028, but potential investments in enhanced features will be focused on the two latest Microsoft D365 products.

 

Making the transition to cloud ERP comes with a slew of advantages. It offers a reliable, scalable IT infrastructure and enhanced integration capabilities, allowing wider implementation of digital transformation technologies. Moving to the cloud, on the other hand, would necessitate yet another large project, with all of the associated expense, difficulty, and risk. How do companies navigate the process to achieve beneficial outcomes while staying within budget and risk constraints?

 

Some of the best practices for migration to Microsoft Dynamics 365 include:

- Starting the Process Early

Despite Microsoft’s determination to support its legacy Dynamics products for at least another eight years, business leaders should begin considering cloud migration now. The big picture of the migration process allows companies to better prepare for the future and divide the process down into smaller steps that are easier to handle and lower risk. Companies can better identify their needs if they provide enough time for thorough preparation and review. This includes determining which Microsoft D365 components the new platform would need. Microsoft is using a more flexible licensing model for its cloud-ERP apps than it does for its legacy on premise ERP applications.

 

Microsoft D365 Finance and Operations, for example, is made up of two main parts: Microsoft D365 Finance and Microsoft D365 Supply Chain Management. You may buy user licenses for specific subgroups of the entire experience, but they function together as a cohesive whole. As a result, rather than paying a premium price for unrestricted access, you’ll only pay for the features needed for each user. Current Microsoft Dynamics customers are eligible for discounts, which should be noted by business leaders. Microsoft has encouraged consumers to make the transition by providing competitive subscription rates to customers of their current legacy ERP solutions, while the company seeks to rapidly expand its position as a pioneer in cloud ERP.

- Deploying a Test Setting

Customers usually also create vendor specifications to simplify the management of incoming inventory. Electronic Data Interchange (EDI) is the default for obtaining the sales order and delivering advanced shipping notices (ASNs) to customers used by big-box retailers. Larger consumers also enforce barcoding conditions. Although those are well-known examples, large companies are increasingly requiring suppliers to adhere to other requirements as well. Walmart declared its plan to reduce CO2 emissions in 2017. Project Gigaton, as the program is called, aims to reduce the company’s carbon footprint across the supply chain. In other words, Walmart will demand that its suppliers keep track of the carbon footprint of the goods they sell to the company.

 

Only a few ERP vendors have built processes into their software to monitor this type of data. It is starting to happen in the biggest, most costly programs, but for most organisations, the problem can be solved with a blend of custom user-defined fields and versatile reporting tools. Whatever potential requirements can entail, reporting tools may help companies remain in compliance.

- Divide the Project

Trying to break up a cloud-ERP migration into smaller chunks is a smart idea for business leaders. This may include initiatives that can be done in advance, providing immediate benefits to the company and a reduction in cost and risk when it is time to migrate the ERP to the cloud. An improvement of reporting tools, procedures, and designs is another big project that you can do ahead of time. This is simpler than it seems, and it’s particularly critical in the sense of migrating to Microsoft D365 in the cloud because Microsoft is making significant technological improvements to the way you manage data for reports and also the reporting set of tools for its ERP applications.

 

Microsoft has limited direct access to the Microsoft D365 F&SCM server to boost security, substituting it with an abstraction layer made up of “data entities.” The new strategy to migration to Microsoft D365 F&SCM necessitates a significant investment in the creation of data entities that will push reporting against the cloud-ERP framework. The effort would necessitate highly trained technical experts and will take a long time. Microsoft’s latest reporting strategy is motivated by the company’s willingness to transfer customers to Azure Data Lakes and Microsoft Power BI.

What can Global Data 365 Offer for Migrating ERP to Microsoft Dynamics 365?

The reporting and analytics tools from Global Data 365 minimize complexity, lower costs, and reduce the possibility of lengthy implementations. They remove the need for experts by allowing finance, accounting, operations, and other departments to generate and adjust reports without relying on IT. We have advanced reporting and analytics solutions that integrate with more than 140 different ERP software systems, including the entire Microsoft Dynamics product line. One of them is Jet Analytics. It greatly simplifies and reduces the expense of cloud migration. Reports produced for legacy systems Microsoft Dynamics products can operate in the Microsoft Office D365 setting without a lot of changes.

 

Schedule a personalized demo with one of our Jet experts. Contact us now.

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We are the authorized distributor of insightsoftware in Middle East. We have worked with 100+ companies in solving their reporting pain points and are committed to providing companies with fast and convenient data access methods from Microsoft Dynamics ERPs using insightsoftware's products and Microsoft Power BI.

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Latest News
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+971 52 843 3085

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