Microsoft continues to be the global leader in solutions for data analytics and Business Intelligence (BI). Integration of industry-leading products such as SQL Server and Power BI with the enterprise-class ERP solution Dynamics 365 for Finance and Operations is driving digital transformation. The latest Gartner Magic Quadrants place Microsoft out front in three categories.
1. Data Management Solutions for Analytics (DMSA)
Gartner defines DMSA as a complete software system that supports and manages data, usually in databases. Microsoft offers a complete data management platform through SQL Server 2017 and powerful Azure cloud services, with support for machine learning and programming languages such as Python and R. Gartner noted that customers, “were generally pleased with the value for money they received from Microsoft.”
2. Analytics and Business Intelligence Platforms
Microsoft, once again, is the undisputed heavy-weight champ of Business Intelligence platforms. The BI market has been transformed by a wave of disruption over the last 15 years, moving away from IT-centric system of record reporting to business-centric agile analytics with self-service. More recently, another wave of disruption has brought augmented analytics, with machine learning generating insights on increasingly vast amounts of data.
Microsoft Power BI offers data preparation, data discovery, interactive dashboards and augmented analytics via a single product. The Gartner report made particular note of Power BI’s low price, ease of use and visual appeal, and was scored highest by customers for “achievement of business benefits”.
3. Operational Database Management Systems (OPDBMS)
The OPDBMS market includes relational and nonrelational DBMS products. Gartner defines a DBMS as a complete software system used to define, create, manage, update and query a database. Microsoft SQL Server DBMS and Azure SQL Database lead the field, with Microsoft receiving the highest reference customer scores of all vendors for “overall experience, meeting needs, value for money, negotiation experience, integration and deployment, service and support, professional support, ease of programming, and tunable consistency.”
Implementing a new ERP system in an organisation is always a challenge. Users question whether they will be able to cope with analysing the data flow in an integrated system without external support. The accountant wonders whether all the set-up accounts are correct. The chief technologist cannot get rid of troublesome thoughts about whether the routings and boms are set up optimally. This is why it is so important to have a reliable service team to help the company control the system in the post-implementation stage. In this article, we take a look at the issues surrounding the implementation of an ERP system and the benefits of maintaining proactive service support.
328.77 million terabytes of data are generated every day - this is the estimate for the first quarter of 2023 (1). These are massive amounts of data on a global scale. On a smaller scale, such as an enterprise, it's difficult to estimate because it depends on the organisation in question, but one thing is certain - collecting, processing and analysing this data is the key to business success today. Why is the Data Lake service so important for data analysis and reporting in Microsoft Dynamics 365 Finance and Operations? How can you tame the data by integrating Microsoft Power BI analytics with Data Lake? We have drawn up some tips.
The retail industry is still dealing with the effects of the pandemic that lasted almost three years. In addition to this, further global events are causing disruption to the supply chain or financial stability of many retailers globally. As the industry confronts new challenges shaped by economic and geopolitical factors, it also faces trends influenced by changing customer expectations and needs. Here are 5 developments and trends to watch.
An interactive, AI-powered support for sales, customer service, marketing, and supply chain - Microsoft Dynamics 365 Copilot leverages generative AI and natural language processing technology to perform simple, yet time-consuming daily tasks that workload employees but can be automated.