Three JDE Reporting & Analytics Trends for 2019

January 31, 2019 | by David Kettinger

2019 will continue to see modern BI & self-service analytics grow in importance for JD Edwards enterprises

In 2018 organizations continued to adopt policies and technologies in efforts to become increasingly data-driven and establish a “data culture” within their companies. As organizations that rely on JD Edwards ERP—along with every other company—saw data volumes explode and an increasing number of employees need access to critical information, modern BI and self-service analytics shifted from being a department-level concern to an enterprise-wide issue. Organizations are starting to migrate their JDE data into public cloud environments to reduce the cost of maintaining legacy data warehouses and to make data more accessible. With Microsoft’s leadership position in modern reporting and analytics tools coupled with their aggressive selling of Office 365, an ever increasing number of JDE customers have started to adopt Microsoft Power BI to deliver modern reporting and BI insights in their business. 

With 2019 upon us, here is what we see coming in the data analytics space this year.

1. The use of modern BI and reporting tools will spread beyond finance teams. Feeling the pain of lengthy close times and clunky spreadsheets that aren’t up to the task, finance analysts are often the first to adopt modern BI and reporting tools. The right software can reduce the time it takes to close the books from days to hours, while empowering users to find data and build dashboards to answer their own questions rather than relying on IT.

Once other functional teams see the benefits that finance users realize by using self-service analytics tools such as Preferred Strategies QuickLaunch™ Microsoft® Power BI with the JD Edwards GL, AP, and AR modules, they want to expand the use of these tools to Sales, Procurement, Manufacturing, Inventory, and beyond. We see the trend of cross-functional adoption of modern BI and reporting tools continuing—and accelerating—in 2019.

Learn how leading companies have reaped the benefits of self-service analytics.

2. Microsoft Power BI will continue to build its position as the self-service analytics tool of choice. In Gartner’s 2019 Magic Quadrant for Analytics and Business Intelligence Platforms, Microsoft was positioned as a leader, and furthest to the right and top for both completeness of vision and ability to execute within the Leaders quadrant. Microsoft continues to make huge investments in Power BI, demonstrating its commitment to innovation. Power BI offers comprehensive analytics capabilities paired with ease of use, plus the security, governance, and compliance features to keep data secure and control how it is accessed and used.

Get the Gartner 2019 Magic Quadrant for Analytics and Business Intelligence Platforms.

3. AI and machine learning will increasingly be democratized as analytics tools, such as Power BI, incorporate built-in machine learning capabilities. Predicting the future of your business is getting easier all the time. There are even new business titles, such as Citizen Data Scientist, that suggests that the brain trust of the past is becoming more mainstream. The reason for this evolution of BI and analytics is the emphasis of the tool developers on acquiring new users and expanding the value of the investment – oh, product differentiation plays a big part too. AI is front and center in this revolution, with tools such as Microsoft Power BI leveraging the $Billions that Microsoft is investing in AI technologies for their Azure cloud platform. Of course the predictive insights won’t flow at all if there is no connection to JDE data and the ability to interpret the legacy data structure into something consumable by these predictive modelling and data science platforms. Fortunately, QuickLaunch bridges the gap between the JDE data and these modern tools so you can start predicting the future of your business. Next up: “Alexa, what’s my current as of aging report for each business unit?”

Learn more about machine learning for JDE data.

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