As we reflect upon 2018, it’s been a tremendous year of technology innovation and product momentum for Magnitude. We’ve invested in significant capabilities to help businesses address mission critical challenges across the enterprise data lifecycle. 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
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.
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
I’ve worked with the Kalido heritage products since the late nineties. Sometimes I’m asked how being part of Magnitude has helped our products like Magnitude DIW and Magnitude MDM. One of the first examples was using the Noetix METL connectors to automatically build the semantic layer for some of the business intelligence tools. We used to use another method to do this that we had to pay extra for and didn’t fully control. If a customer asked us to change something, we had to raise the issue with the provider we used and then were at the mercy of their schedule to implement it (and in the worst case, sometimes denied the request). Fast forward to using METL, we now control the end to end process and could take advantage of other BI tools that METL supports in the future. Read more
Some of the most frequently asked questions we hear from our customers are:
- Why do I need another MDM application?
- What are the differences between MDM and PIM?
- Do I really need an MDM and a PIM solution?
In many ways, these questions are based upon a faulty assumption, namely that product data management (PIM) and Master Data Management (MDM) are the same thing. While are closely related, but they are most certainly not the same – at least if you subscribe to our definitions of PIM and MDM. In our view MDM has several goals: Read more
I read with interest a Gartner report, Modern Data Management Requires a Balance Between Collecting Data and Connecting to Data, that made the case for a bi-modal approach to connecting and collecting data. The case being made is that being able to react “at the edges” of broader data infrastructure (making decisions based on real time data displayed on a tablet, for example) requires direct connection of processes and devices, while collection of data for operations and management insight requires a central collection point and rigorous validation of data accuracy and quality. However, ALL data requires a series of integration processes that describe, organize and integrate the information. That first step, the description, includes the location, trustworthiness and meaning of the data in question. Read more
It seems these days that everyone is looking for a “360-degree view” of customer, product, vendor and just about every category of information you can think of. However, getting there is not always so easy, and gets harder as organizations get larger.
Today, very few organizations have only one operational system, and many have several. It is not uncommon for us to encounter clients with 3, 4 or more ERPs, not to mention other legacy applications and data sources. As these systems grew over time they became more and more siloed, with each system focusing on a different view of data, all of which much be reconciled and combined. How do we integrate say, customer data, from 4 or 5 sources when there are no common identifiers and even things like names and addresses are inconsistent in format or spelling? Read more
Magnitude puts a lot of emphasis on ensuring customers get the most out of our software. Of course, it’s a major focus during the initial deployment, but equally important, if not more so, is an ongoing checkpoint of whether our customers are hitting the targets they have defined for themselves. Read more