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Cash Flow Analysis with Microsoft BI
Blogs

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! 

Talk to our BI Experts!

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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! 

Talk to our BI Experts

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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.

Get 30 Days Free Jet Analytics License!

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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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ways to optimize your ERP reporting
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How to Optimize Your ERP Reporting?

ways to optimize your ERP reporting

According to a recent study, nearly 81% of companies surveyed reported that they had either introduced the use of ERP software or were in the process of implementing it. So, what makes ERP reporting important? By leveraging ERP data analysis, businesses can create strategic plans, forecast future trends, and develop advanced strategies. To truly maximize these benefits, it’s essential to optimize your ERP reporting for more accurate insights and decision-making.

 

A depth of data indicates that financial reporting generates as much clarification as it creates confusion:

 

97% of CFO’s have uncertainty regarding the quality of reporting.

 

  • 40% of CFO’s are concerned that information is reliable and precise.
  • 87% of accountants function overtime to complete the financial closing.
  • 86% of finance teams say that their analytics are not informative.

The only downside is that companies cannot be successful if they don’t have reliable, accurate, and detailed ERP reporting, which can lead to them making risky choices without even acknowledging it. The plus side is that optimizing ERP reporting is not a difficult task in comparison to the usual reporting process.

 

Listed below are the 5 ways businesses can optimize their ERP Reporting to make it quick and easy:

Self-Service Reporting

Users often need to submit a request to IT before getting access to a report and wait in a queue until they can access it. Users must depend on technical experts because working with the underlying data is hard. For users who are not IT experts, self-service ERP reporting is intended to be user-friendly. This kind of reporting is less about the careful organization of data and more about being cost-effective and a time saver.

 

For instance, IKEA, one of the biggest retail company has enabled self-service ERP reporting after the implementation of Jet Reports and witnessed instant results. A report that may have taken hours for a warehouse manager can now be done within seconds. Time is saved by enabling self-sufficient ERP reporting.

Automated Processes

A large-scale data organization effort is required to report on finance and operations throughout different departments. The workload includes tracking information from different sources, transferring it from one document to another, and putting time and effort to arrange it all in one clear performance portrait. Advanced automated processes speed up this effort by automatically placing data from ERP systems and other networks, then placing it for immediate analysis into pre-built ERP report templates.

 

Amref Health Africa, a major NGO in Africa, was having difficulty handling data manually before adding Jet Reports to its reporting toolbox. Now the organization spends less time on handling information and reporting.

Flexibility

Reporting is a regular duty that changes with time. Depending on the same reports adds up to poor performance management, but it takes extra time and feedback from IT experts to produce customized reports. ERP reporting stops being a hassle when it is simple to track various metrics, rewrite reporting data, receive deep insight from reports into transferable data, and access real-time updates on request.

 

Using an ERP reporting tool, companies can keep track of their data in real-time. Fawaz Holding seized the benefit of customized reports when it introduced Jet Reports to operate side by side with its Microsoft Dynamics 365 Business Central ERP. By building flexibility into the processes, ERP reporting becomes easier.

Business Continuation

Accurate ERP reporting is vital after the global pandemic. Decision-makers instantly require quality, updated data, but it can also be made inaccessible by the same situation that makes it essential. ERP reporting should function at any time, providing the same robust functionality even though users are operating from elsewhere.

 

Similarly, Enova Facilities Management started to save time on ERP reporting using Jet Reports. When COVID-19 struck, the business utilized those time saved. The challenge didn’t sway the method of reporting, instead, it provided leaders greater insight into the situation.

Higher Standards

ERP reporting can be difficult when the processes are not automated. It leads to a lot of time and effort spent on manually documenting reports and generating analysis. Many ERP reporting systems allow the users data security. It is important to set high standards for data reporting, so businesses need to implement robust ERP systems to automate processes and receive greater insight into the workings of all departments.

 

Air Trade Centre, a Turkish electronics firm felt it needed quicker ERP reporting and relied on Jet Analytics as the solution. After that, reporting then demanded 60% less feedback overall, which reduced the time it took IT on reporting.

In Conclusion

Learn How to Optimize Your ERP Reporting as accurate reporting is a result of quality data, which is precisely the reason the process takes time. Data is an unruly commodity that takes an extra effort to control, protect, and manipulate. As the data volume grows, ERP reporting will fall behind and cause companies to delay acting. That is why it is important to search for strategies that make data as quickly available as possible by automation.

 

So, if you face any challenges in reporting, our experienced consultants can provide you with solutions to help you optimize your ERP reporting and make your business grow. Schedule a call to discuss your requirements. Contact us now.

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Risks to Your BI Implementation
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Why BI Implementation Can Be Risky?

Risks to Your BI Implementation

Gartner recently published a study on all the stuff that can go wrong with your BI implementation. We have classified them into 8 different risks to your BI implementation based on our team’s insights here at Global Data 365. These risks can easily be overcome, but they are very likely to infiltrate your business plans. 

 

An analyst in Gartner’s report takes great pains to stress that there is far more risk associated with non-technology problems than there is with implementing infrastructure, resources, and applications. Listed below are the 8 different risks of BI Implementation; so you can recognize them and avoid potential problems in the future. 

-Building a Project with BI Implementation

Starting a business intelligence project with this mentality means that the program is funded by IT and is usually led from a technological or data-centric viewpoint. The issue is that BI Implementation is being driven by IT rather than the company. Unless IT has a strategic plan or a consumer case of their own to include here, they aren’t interested in the final consumption of the BI deliverable and can only play a minor part in the development. 

 

The solution is to ensure that the project team includes a marking scheme from the business side of the house from the start of the planning phase through infrastructure upgrades. 

- Excel Culture

The second potential risks can be Excel. With Excel, you collect data from an internal structure, load it into Excel, and manipulate the figures. Every single person who participates in this would have a different point of view for the BI Implementation. Different methods of converting numbers into metrics will be used. They may also have opposing goals. You’ll get different results from each, and your data will be totally inaccurate. To us, that just means one thing: risk. The company is at risk. It’s the danger that comes with making costly decisions based on inaccurate knowledge. 

 

The solution is to build a data warehouse. This will be the location where everyone has settled on the data that will be used to handle the company, as well as how that data will be combined with the methods that will be used to measure items like total revenue and net income. 

- Issues in Data Quality

Everyone deals with issues in data quality. The problems that trigger it are various, and their effect on business intelligence is important. This is because people would not use BI software based on data that is meaningless, incomplete, or suspicious. 

 

Establishing a process or collection of automated controls to detect bad data and prevent it from entering the data warehouse or BI environment is the solution. Surprisingly, a BI implementation can solve this problem all by itself. It’s because having data quality problems in a dashboard will draw attention to them. That should give you a good idea of how to track them down. Learn how to plan your data for business intelligence.

- Diverse Options

You’ll be confused if you search “BI solutions”, attend a related tradeshow, or read quite a lot of BI reports. There are several options available. But how do you know which approach to business intelligence or that the BI implementation is right for you? 

 

The solution is to avoid putting the cart before the horse. First, assess the requirements. Evaluate them from a market and a technological standpoint, and then use the results of that exercise to guide the quest for approaches and solution providers. 

- Using Existing IT Provider

BI is unlike any other project. Since you’re working with human beings and their methods, as well as the changing conditions of the business world, there’s a little luck involved. We are convinced that a business that specializes in BI projects will not be able to help you succeed. Seeking a business that specializes in BI environments is the safest approach. For this, you’ll need a professional. 

 

If you’ve decided that they have the technological experience and track record to make you happy, if you want to be good, don’t be afraid to evaluate them on fit, desire, and dedication. Those are the things that are more difficult to determine, but BI implementations usually last a long time, so it won’t cause you any problem.  

- Time in BI Implementation

The other threat is about the time it takes in your BI implementation. A BI project can be placed into a low-cost maintenance state, but your company will never stop evolving, and because BI is built to model your business, it must also change. 

 

Having demands is one way to avoid this from being a concern. You should anticipate that the BI success would be a moving target over time. Let everyone know how things will pan out. Prepare for it by scheduling deliverables and budgeting for it. 

- Insufficient Training

Many companies spend all their BI budgets on software applications and a few weeks of user training. Today’s BI systems, on the other hand, are dynamic constructs that need much more training for users to derive true value from them. Besides, continuous training is needed to ensure that users are familiar with and comfortable with the system. 

 

Furthermore, companies should ensure that the software they install contains online training videos that help users become more comfortable with the current BI framework or the companies should opt for online training of the BI Software they use. 

- Data Collection from BI software

Some businesses gather useful data from their business intelligence tools but don’t distribute, evaluate, or act on it. When deciding what to do with BI implementation, it’s important to think outside the box. Companies may avoid risk and make educated decisions to move their industry forward by using the knowledge collected and adapting it to their own business models. 

Companies can use BI software on different data points, analyze risks, and predict trends. To improve the reporting capabilities of their BI software, companies should be able to identify risks and predict trends. 

Having a Strategy

Not having a BI strategy can be one of the biggest threat to your BI implementation. BI strategy can change the way you collect, analyze, and deliver data. As everyone works on the same KPIs to drive action and optimize processes, there is no chance of manual error. 

 

Global Data 365 It helps you with its experienced team who considers all the potential risks and avoids them during your BI implementation. To discuss your requirement, speak to one of our BI experts. 

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Limitations of Power BI
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Limitations of Power BI – Are They Risky?

Limitations of Power BI

If your business is considering implementing Microsoft’s Power BI analytics framework, you must understand the level of complexity and limitations of Power BI involved in successful integration. Power BI is a many-month software project based on a complex mix of technological elements, not just a device you install and customize. To get it right, you’ll need a lot of preparation and the highest level of management skills. So, what is Power BI and what are some limitations of Power BI?

Power BI

Microsoft’s Power BI is a cloud-based business intelligence service package. It uses insightful visualizations and tables to transform raw data into usable information. Data can be processed and used to make strategic business decisions in a short amount of time. Power BI is a set of business intelligence and data visualization tools that includes software services, applications, and data connectors. Power BI is a user-friendly tool with versatile drag-and-drop design and self-service capabilities. Power BI can be used on both on-premises and cloud systems.

So, what are the limitations of Power BI that you can avoid?

What is Jet Reports?

Jet Reports, on the other hand, is a dynamic business intelligence tool that goes beyond conventional financial reporting. With its user-friendly interface and Jet Dashboard Designer, organizations can leverage its capabilities for comprehensive financial reporting and analysis. Jet Reports is known for its adaptability and ease of use, making it an asset for businesses aiming to enhance their reporting processes. 

We are going to give you three scenarios where a user should consider switching to Jet Reports or Jet Analytics: 

Complexity Involved with Power BI

Most of us have become used to applications that can be downloaded in minutes or even hours in the case of more advanced systems. That’s a fairly straightforward scenario. At the other side of the curve are items that entail some configuration and are designed and implemented by a team of specialized experts to overcome the limitations of Power BI. A full Power BI implementation must solve a slew of design issues. The answers to those questions will affect efficiency, productivity, and adaptability in the long run. Some of the major differences between a Power BI cloud deployment and an on-premise deployment. For instance:

 

– What features should you run, where should they run, and how will they all interact?

 

– What level (or levels) of security do you incorporate?

 

– Will you be using SQL Server Analysis Services to model your results, or will you use the Power BI desktop tool?

 

– Should you use Power BI’s Direct Query function or import data?

 

– Will a gateway component be needed, and if so, where will it be installed?

 

All these are technical questions, but the solutions have long-term consequences, and it’s always difficult to adjust later. This level of complexity necessitates upkeep, which entails additional costs and disruption.

Power BI: Toolset not a Complete Solution

There are no reports included with Power BI out of the box. In fact, Power BI reporting necessitates a substantial upfront expenditure, not just in terms of constructing the technological infrastructure, but also in terms of deciding how you access the data, how and when data must be converted or pre-processed, where you archive them, and so on. After you have answered those design considerations and limitations of Power BI, you will need to put in a lot of time to set up the data access and data flow.

 

Data access is becoming more complex in this age of cloud computing. This is particularly true of Microsoft Dynamics 365 products, which no longer require unlimited reporting access. Microsoft has suggested some possible workarounds, but all of them require major compromises. Microsoft has introduced an indirect layer of “data entities” in Microsoft Dynamics 365 Finance & Supply Chain Management (D365 F&SCM), for instance, that developers can use to obtain entry to ERP data. Personalizing Power BI can be very costly. Since every company is different and has its own set of requirements, customization is unavoidable. Recurring costs arise from the ongoing maintenance of such customizations.

Power BI as a Dashboard Visualization Tool

Power BI was developed to be used as a dashboard visualization tool. It does an adequate job of producing conventional tabular reports, lists of individual records with several columns and subtotals, and it does a great job of providing an insightful visual analysis of what is happening in the market. Traditional banking statements are not generated by Power BI because they are somewhat different from other forms of reports. Some more limitations of Power BI such as Filtering, masking, or grouping GL sums by account column, for example, is commonly required when creating a P&L statement. This is often done in different ways for each row in the report.

 

Columns in the report may be sorted by organizational agency or division, or they can be used to reflect various time spans, budget vs. real, or variance amounts or percentages. Since Limitations of Power BI has a little method of controlling such distinctions, having it generate a comparatively straightforward P&L is a very costly custom programming activity.

Power BI without the Limitations

Global Data 365 offers self-service, user-friendly analytics and reporting tools, as well as collaboration with Power BI and Excel. With the help of Jet Analytics, we hold the guesswork out of Power BI by automating the process of developing a data warehouse with pre-built connectors for over 140 different ERP systems, allowing business leaders and analysts to have the data they demand, when they need it, without any need for specific commands or the complexity and limitations of Power BI stack.

 

Need to overcome the limitations of Power BI, opt for our Power BI Training program today.

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Why Is Good Data Management Essential For Data Analytics
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Why Is Good Data Management Essential For Data Analytics?

Why Is Good Data Management Essential For Data Analytics

Today, Businesses have more data at their disposal than ever before. Over time, businesses that can efficiently use data as a strategic advantage can eventually achieve a competitive edge and outperform their rivals. Business administrators, on the other hand, must add order to the chaotic world of various data sources and data models to do this. Data management is the general term for this method. Data management is becoming an essential component in successful business management as the amount of available data grows.

On the other hand, a lack of effective data protection can lead to incompatible or unreliable data sources, as well as data quality issues. These challenges can hinder an organization’s ability to derive value from data-driven insights, recognize patterns, and spot problems before they become major issues. Worse, bad data management can lead to managers making decisions based on incorrect assumptions.

Availability of Data

The emergence of systems, such as ERP, CRM, e-commerce, or specialized industry-specific applications, is causing such problems. When you add web analytics, digital marketing automation, and social media to the mix, the data volume skyrockets. When you add in external data from vendors and service providers, it becomes unmanageable.

 

Many businesses understand the importance of using externally sourced third-party data to supplement and extend the context of knowledge they already have. However, it’s difficult to imagine taking that step without first having a grasp on the organization’s current data. Bringing all of this uncertainty under control is a key first step in implementing a strategic data analytics program. That is a two-step method from a high-level perspective. To begin, you must collect all of the data and store it in a centralized location. This includes filtering, transforming, and harmonizing data so that it blends to form a coherent whole.

Secondly, the data must be available to users around the enterprise so that you can put it to good use and add value to the company. In other words, you must implement processes that allow users within the organization to access the information easily, efficiently, and with enough versatility that they can evaluate and innovate without extensive IT training. To ensure efficiency, you must identify and implement these two aspects of data management individually. Flexibility and usability result from a pre-built data management process and interface; the quicker you assemble and clean up the data, the easier the data will start producing value for the business.

Multiple Systems

When a company runs several processes, data processing becomes a problem. As previously stated, this may include ERP, CRM, e-commerce, or any other software framework. It’s also usual for many companies to use several systems to accomplish the same job. Different ERPs may be used by different divisions or corporate agencies operating under the same corporate name. This is especially true when it comes to mergers and acquisitions.

 

Many businesses would like to perform reports against historical data stored in a defunct database. Since migrating accurate transactional data to a new ERP system is not always feasible, many companies use a workaround or simply go without, leaving important legacy data out of their existing reporting systems. Multiple data models are invariably present when multiple software systems are involved. A clear report detailing all of the company’s customers becomes a little more complex. If one ERP system has different tables for clients and vendors, while the other merges them into a single table (using a single field to classify them as customers, vendors, or both). Before loading data into a centralized repository with a uniform approach of the customer, you’ll need to extract and transform data from those two ERP systems. The process must include a type of translation in which data structures and semantic models are aligned.

Extracting, Transforming, and Loading Data

The term “ETL” refers to the method of processing, converting, and loading data into a central repository. ETL is one of the most important aspects of a data warehouse, and it’s necessary for businesses who want to provide dependable, scalable, and reliable reporting. A data warehouse that embraces a complete view of data from across the enterprise, irrespective of which system it came from, is the end product of a very well ETL process.

 

This procedure often connects records that are spread through different systems. It is normal, for example, to designate master records with unique identifiers that aren’t always consistent across two or more systems. The central repository must link those two documents and classify them as the same individual to create reports that provide a full image of that customer.

Diverse Options

You’ll be confused if you search “BI solutions”, attend a related tradeshow, or read quite a lot of BI reports. There are several options available. But how do you know which approach to business intelligence is right for you?

The solution is to avoid putting the cart before the horse. First, assess the requirements. Evaluate them from a market and a technological standpoint, and then use the results of that exercise to guide the quest for approaches and solution providers.

Self-Service Reporting and Data Visualization

The second important aspect of good data management is to make information readily available to users across the enterprise. Provide them with resources that allow them to innovate and add value to the company. In fact, data visualization tools are becoming a strong tool for informing, aligning, and encouraging leaders across entire organizations. Data visualization tools are now simpler to deploy, maintain, and use than ever before.

 

Until recently, installing and maintaining a data warehouse facilitated a significant investment in highly specialized technical services. A reliable computing infrastructure capable of handling the necessary workloads. Legacy tools necessitated a thorough understanding of the source data as well as meticulous preparation ahead of time to decide how to use the resulting data. Modern data visualization tools are extremely efficient and adaptable, requiring far less advanced IT knowledge. Many of the tasks associated with designing dashboards, graphs, and other visualizations can now be performed by frontline users who communicate with the data daily.

Good Data Management with Jet Analytics

Both aspects of the data management process as described here, are provided by Jet Analytics from Global Data 365. For starters, it offers a robust framework for constructing a data warehouse. With developing and managing the ETL method, bringing data from various fragmented systems under one roof for simple, relevant reporting and analysis. Along with that, Jet Analytics provides a robust reporting package that allows practically everyone in the company to create powerful visual dashboards, analyses, and ad hoc analysis.

 

To find out more about how Jet Analytics can help your company manage the complexity of multiple data sources, contact us.

Get 30 days free license for Jet Reports.

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Why-Power-BI-Is-a-Better-Choice-than-Excel-for-Analytics
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Why Power BI is a Better Choice than Excel for Analytics

Why-Power-BI-Is-a-Better-Choice-than-Excel-for-Analytics

Modern businesses depend on data, and we’re producing more of it than ever before. However, accumulating vast volumes of digital data is useless unless companies can leverage it effectively. Business intelligence tools, such as Power BI and Excel, can play a crucial role in this process.

 

Are you planning to introduce a platform to assist you in extracting valuable, actionable insights from your data? You have arrived at the right place. By harnessing the capabilities of Power BI and Excel, you can transform raw data into meaningful visualizations and reports, empowering your organization to make informed decisions based on real-time analytics.

 

Explore how Power BI and Excel can work together to unlock the full potential of your data, streamline your reporting processes, and enhance your business strategies. Let’s embark on this journey to data-driven success! We will go over the fundamentals of Microsoft’s flagship BI app, Power BI, in this article, like what it can do, what it costs, and what changes it can provide to your company.

Characteristics of Power BI Desktop

– Can link to several different data sources. With the Auto-Refresh option, you can keep this data up to date.

– It aids in the rapid modelling of data.

– Using the drag and drop map, it is possible to generate interactive reports.

Characteristics of Power BI Service

– It is a web portal that allows users to monitor and view reports generated with Power BI Desktop.

– Reduce the amount of time spent moving and sharing information.

– Data can be imported from a variety of on-premise sources (Excel, DB, CSV, etc.) or directly documented from a variety of cloud web services, including Azure, MailChimp, Zendesk, and Salesforce.

Why should you Choose Power BI over Excel?

Power BI has many benefits to offer compared to Excel. Listed below are some of the benefits.

- Convenience and Data Size

Power BI can handle massive amounts of raw data as well as several data tables. The analytical tool is capable of loading and processing large amounts of data into a single PBIX file. Multiple tables can be configured and, if necessary, combined based on common fields. In terms of user interface and ease of use, the Power Query Editor and Data Modeling parts are easier to use.

- Data Connectivity and Auto Refresh

One of the key reasons to use Power BI is that it can link to a broad range of data sources, including databases, online sites like Facebook, and Salesforce reports, among others. When compared to the previous data, the data is automatically inserted into the Power BI Workbook. Excel’s ODBC Driver takes up a lot of time.

 

Power BI has a great choice for keeping data in alignment with the source called Auto Refresh. To have all the reports updated, Power BI Desktop has a Refresh option, and Power BI Service has a Refresh Now, as well as a Scheduled Refresh option. When you choose Refresh, the data in the file’s model is replaced with the most recent information from the original data source. This form of a refresh, which takes place entirely inside the Power BI Desktop program, varies from Power BI’s Refresh Now and Scheduled Refresh solutions.

 

Power BI uses the information in the database to link to the data sources identified for it, search for updated data, and then upload the updated data into the dataset when you refresh data in a dataset, whether using Refresh Now or setting up a refresh schedule. In Power BI, unlike Excel, the dashboard can be refreshed.

- Reporting and Cross-Filtering

Power BI reporting is much more advanced and engaging than Excel reports, and a single graph can provide numerous perspectives. In Excel, cross-filtering is not possible, but it is possible in Power BI. This has an impact on how users want the filtering for data with table relationships to move.

- Alerts and Emails

To submit a mail and a reminder in Excel, a user has to use the VBA Editor to generate a macro. In Power BI, creating a warning and sending an email when a condition (such as a threshold value) is met has never been easier. This will keep users updated when on the move, and they will be able to view the report at any time and from any place.

 

Some other features include:

 

  • Natural Language Query (NLQ): By asking a common person question in Power BI Service, everyone can get a fast response from the current insights. It’s helpful when someone isn’t familiar with the data model but needs fast answers to questions about the insights. Furthermore, this saves a lot of time.
  • Deeper Insights: The backend program, which is driven by intelligence and algorithms, can generate interactive insights at the touch of a button. It will help you save time and interpret data more quickly.
  • Dashboards and Customized Reports: The reports produced can be modified to achieve the desired outcomes. On the dashboard, the report tiles can be rearranged and relocated as desired.

  • Sharing Reports and Access: The reports and dashboards may be shared with the public or only a small group of associates.
  • Downloading and Exporting Dashboards: The Power BI Service lets you download and transfer dashboards in various formats. The dashboards can be submitted as a .PBIX file or exported as a PowerPoint presentation, PDF, or event print.

In Conclusion

In today’s data-driven environment, a fast and efficient data analytics tool is needed. Power BI makes use of business intelligence to ensure that all reports are produced efficiently and provide a wealth of information. Changes in time and technology necessitate the use of a versatile tool like Power BI, which makes work easier and saves time while delivering the best performance. Get a suitable power bi training for your needs or for more information, contact us today!

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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.

insightsoftware partner
Microsoft Partner

Solutions

D356 Business Central
D356 Finance & Operations
D356 CRM
Jet Reports
Jet Analytics
Power BI
Power Apps
Power Automate

Resources

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Latest News
Help Center
Become a Partner

Training

Jet Training
Power BI Training

Contact Us

Office # 1912-16, The Binary by OMNIYAT, Business Bay, Dubai, UAE.

+971 52 843 3085

sales@globaldata365.com

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