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The Future of AI in the Business World

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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.

Takeaway

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

Home > Blogs > Migrating from On-Premise ERP to Microsoft Dynamics 365

Migrating from On-Premise ERP to Microsoft Dynamics 365

May 21, 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.

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

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-centred 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 as well as enhanced integration capabilities, allowing for 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 particular needs if they provide adequate 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 consequence, rather than paying a premium price for unrestricted access, you’ll only pay for the features you need 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.

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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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