We’ve all heard the saying “data is the new oil!” In today’s data-driven economy, managing application data effectively is now table stakes for any agile-minded business. But in reality – even with a team of data experts on staff – most companies struggle to keep up with the scale and pace of data creation across the myriad of ERPs, cloud, on-premises and hybrid systems. Read more
With the release of Magnitude MDM 10 SP1 on October 4, 2018, we have completely rearchitected the way we manage and process data. What does this mean to the user? Read on…. Read more
Applying a model-driven approach to data management is key for meeting the speed to market and flexibility needs of today’s businesses.
Rather than requiring a complete model of the entire enterprise-wide set of requirements before deploying the warehouse, Magnitude’s Business Information Modeler (BIM) allows you to start small, iterate, and deploy in increments. Read more
Aggregating and managing all product data is cornerstone for any digital commerce strategy. In the many years since we saw a need to better manage product information and developed the first version of the Agility software, PIM has become a critical technology investment for both IT and business executives. A solid PIM solution helps you to dramatically improve data quality and govern data access and usage. It enables portfolio expansion as your business grows. And, effective product information management provides the flexibility to respond to changing market conditions. Read more
The science of managing information about products has existed for decades, although, Product Information Management (PIM) is a relatively new branch of Data Management. Historically, the solutions required to manage product content have been complex, since that data has multiple touch-points and affects the 3 pillars – People, Process and Technology. With a shift in the industry to promote business-focused, data-driven organizations, PIM was invented with a purpose to ease the collection, management and syndication of data, in a simple, easy and concise manner. However, there are still some myths from its past. Read more
Running your business and analyzing results with accurate and consistent data is mission critical, yet most organizations struggle with bad data. An IBM study estimates that $3.1 Trillion of America’s GDP is lost due to bad data and 1 in 3 business leaders don’t trust their own data.
Now that the initial GDPR deadline has passed, what are companies doing to ensure that they have the steps in place to operationalize compliance?
A recent Gartner report, 2018 Strategic Roadmap for Postmodern ERP, describes how today’s organizations tend to focus on monolithic, vendor-first Enterprise Resource Planning (ERP) strategies that do not support their digital business initiatives. The report further recommends a postmodern ERP strategy that includes the integration of differentiated and innovative capabilities that are beyond the core strengths of the common ERP platforms. Read more
Magnitude was founded on a base of strong ERP knowledge (Noetix), acquired more (Datalytics Technologies), and has recently been accelerating investment in the SAP ecosystem (SourceConnect product) and the purchase of Innowera and Every Angle. With that in mind, I finally got around to reading the Gartner report 2018 Strategic Roadmap for Postmodern ERP by Paul Saunders, Denise Ganly, and Mike Guay. This report states that organizations tend to focus on monolithic, vendor-first ERP strategies that do not support digital business initiatives and recommends a postmodern ERP strategy that includes the integration of differentiated and innovative capabilities that are beyond the core strengths of the common ERP platforms. Read more
At this year’s Strata Data Conference, Magnitude unveiled its breakthrough data connectivity solution, Magnitude Gateway with customers and partners. We caught up with data analytics thought leader and TreeHive Strategy principal, Donald Farmer on his perspective on data connectivity and Magnitude’s new offering. Read more