How can IT be removed from Financial Reporting

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How can IT be removed from Financial Reporting?

July 26, 2021

Global Data 365 is composed of highly skilled professionals who specialize in streamlining the data and automate the reporting process through the utilization of various business intelligence tools.

How can IT be removed from Financial Reporting

If you are asked to present up-to-the-minute information on cash flow, chances are you would create a worst-case scenario based on some new assumptions, such as a 20% decrease in sales and a 15-day delay in collections. Even though you’ve generated hundreds of cash flow reports, you’ve never been asked for this exact version before. It requires some additional details, such as a sales pipeline review and improvements to the aging study. Almost anyone who has ever worked in finance or accounting has encountered a situation like this at some stage. With the coronavirus outbreak, business leaders couldn’t bear to have inefficiencies slowing their access to the information as they tried to evaluate the situation and react quickly.

Eradicate the Chokepoints

To produce or change system reports, the finance and accounting department has mainly focused on IT experts or costly outside consultants. Many accounting and ERP frameworks provide report design tools that are inflexible and require a steep learning curve. This raises a variety of difficulties. For starters, it establishes a reliance on a third-party department. Cross-team dependencies are common in most organisations, but when one department’s goals vary from those of others, conflict or chokepoints occur, preventing work from being accomplished quickly and efficiently.

When a particular department is overburdened with conflicting interests, problems may occur. Many IT divisions were preoccupied with tasks related to the enablement of remote staff as the coronavirus crisis unfolded, for example. This occurred at precisely the moment when C-level executives required the most urgent access to financial data and analysis. Businesses can try to remove these forms of dependencies as much as possible as a long-term strategy, so those cross-functional collaboration strategies will concentrate on areas where teamwork and diverse viewpoints add real value.

Enhance Flexibility

The second issue with conventional reporting tools is that they often lack the versatility that finance and accounting users need. Because of its immense strength and versatility, most F&O users tend to work in Excel. Excel is an excellent tool for manipulating, analysing, and visualizing data. Almost every finance expert knows how to make good use of it. The finance and accounting department will kill two birds with one stone by allowing real-time data from various software systems to be accessed directly inside Excel.

For starters, they may reduce their reliance on technology. Second, they will enable finance and accounting professionals to create reports and conduct analyses using a single, strong, and familiar tool. Many businesses have found interest in implementing web-based dashboards so that leaders around the enterprise can have real-time access to a shared collection of business metrics. A few of these web-based dashboard platforms follow a common user-empowerment philosophy, allowing the finance department to set the agenda and implement a strategy for carrying out corporate dashboards without relying on the IT department in the long run.

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Eliminate Errors

When finance takes over the reporting role, it will be able to address another issue that most F&O teams are familiar with. Traditionally, manually copying and pasting data from ERP, CRM, and other internal systems into Excel was needed for reporting and analysis. It is a time-consuming procedure that is prone to introducing errors into the reporting process. As data source formats alter (for example, when a new row is added to a General Ledger report), data may be pasted incorrectly into a pre-defined Excel template. Expert spreadsheet users will also incorporate error-checking algorithms or workarounds to avoid incorrect results in this case, but such methods are far from foolproof.

Another major disadvantage of the copy/paste process is that it is time-consuming. It generates reports that are based on out-of-date data. Data extracted from a source system, such as ERP, no longer provides an accurate and up-to-date picture of what’s happening in the industry. Data must be updated, and then copy/paste procedure must be repeated to review reports. Building a reporting strategy focused on real-time data access is a safer option.

An Alternative Approach

Take into account this alternative strategy, in which data is made accessible in real-time by connecting to multiple source networks within the enterprise. Because when the finance department can create reports directly in a familiar method like Excel instead of having to copy and paste data from other systems, it can concentrate on what it does best: compiling and evaluating data to make better business decisions.

The need to refresh content won’t arise since this system enables real-time access to information. Direct links to source systems such as ERP or CRM may be used to automatically refresh data. With less effort, less cross-team dependency, and a lower risk of mistakes, everybody gets a real-time view of what’s going on in the company.

All of these advantages are open to companies using several off-the-shelf ERP, CRM, and other software systems due to Global Data 365‘s powerful reporting tools. Reports can be created, updated, and distributed securely within the organization. Users only have access to information that they are allowed to see due to built-in data protection. The year 2021 will see a renewed emphasis on software automation tools. Automation of reporting and related tasks is a reasonable first step for companies looking to improve efficiencies by doing more with less, and remote workers aim to collaborate easily and efficiently with other team members.

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The Future of AI in the Business World

Home > Blogs > The Future of AI in the Business World

The Future of AI in the Business World

March 26, 2021

Global Data 365 is composed of highly skilled professionals who specialize in streamlining the data and automate the reporting process through the utilization of various business intelligence tools.

The Future of AI in the Business World

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 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 also 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 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?

What can 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 have to 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

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:

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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 percent 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 activities, 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 the 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 analysing 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.

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.


In the future, artificial intelligence 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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