8 Information Quality Predictions for 2015 And Beyond
Andy Hayler of Information Difference wrote in October last year that it’s been 10 years since the master data management (MDM) industry emerged. Andy sees MDM technology maturing and project success rates rising. He concluded that MDM has moved past its infancy and has a promising future as it is approaching its teenage years.
The last few months have allowed me to see MDM, data quality and data governance from a completely different perspective. I sat with other leaders here at Informatica, analysts who focus on information quality and spent time talking to our partners who work closely with customers on data management initiatives. As we collectively attempted to peer into the crystal ball and forecast what will be hot – and what will not – in this year and beyond for MDM and data quality, here are few top predictions that stood out.
1. MDM will become a single platform for all master entities
“The classical notion of boundaries that existed where we would say, this is MDM versus this is not MDM is going to get blurred,” says Dennis Moore – SVP, Information Quality Solutions (IQS), Informatica. “Today, we master a fairly small number of attributes in MDM. Rather than only mastering core attributes, we need to master business level entities, like customer, product, location, assets, things, etc., and combine all relevant attributes into a single platform which can be used to develop new “data fueled” applications. This platform will allow mastering of data, aggregate data from other sources, and also syndicate that data out into other systems.”
Traditionally MDM was an invisible hub that was connected to all the spokes. Instead, Dennis says – “MDM will become more visible and will act as an application development platform.”
2. PIM is becoming more integrated environment that covers all information about products and related data in single place
More and more customers want to have single interface which will allow them to manage all product information. Along with managing a product’s length, width, height, color, cost etc., they probably want to see data about the history, credit rating, previous quality rating, sustainability scorecard, returns, credits and so on. Dennis says – “All the product information in one place helps make better decisions with embedded analytics, giving answers to questions such as:
- What were my sales last week?
- Which promotions are performing well and poorly?
- Which suppliers are not delivering on their SLAs?
- Which stores aren’t selling according to plan?
- How are the products performing in specific markets?”
Essentially, PIM will become a sovereign supplier of product data that goes in your catalog and ecommerce system that will be used by merchandisers, buyers, and product and category managers. It will become the buyer’s guide and a desktop for the person whose job is to figure out how to effectively promote products to meet sales targets.
3. MDM will become an integral part of big data analytics projects
“Big data analytics suffers from the same challenges as traditional data warehouses – bad data quality produces sub-optimal intelligence. MDM has traditionally enabled better analysis and reporting with high quality master data. Big data analytics will also immensely benefit from MDM’s most trustworthy information.” – Said Ravi Shankar – VP of Product Marketing, MDM, Informatica
Naveen Sharma who heads Enterprise Data Management practice at Cognizant reemphasized what I heard from Dennis. He says – “With big data and information quality coming together, some of the boundaries between a pure MDM system and a pure analytical system will start to soften”. Naveen explains – “MDM is now seen as an integral part of big data analytics projects and it’s a huge change from a couple of years ago. Two of large retailers we work with are going down the path of trying to bring not only the customer dimension but the associated transactional data to derive meaning into an extended MDM platform. I see this trend continuing in 2015 and beyond with other verticals as well.”
4. Business requirements are leading to the creation of solutions
There are several business problems being solved by MDM, such as improving supplier spend management and collaboration with better supplier data. Supply chain, sourcing and procurement teams gain significant cost savings and a boost in productivity by mastering supplier, raw materials and product information and fueling their business and analytical applications with that clean, consistent and connected information. Jakki Geiger, Senior Director of IQS Solutions Marketing at Informatica says, “Business users want more than just the underlying infrastructure to manage business-critical data about suppliers, raw materials, and products. They want to access this information directly through a business-friendly user interface. They want a business process-driven workflow to manage the full supplier lifecycle, including: supplier registration, qualification, verification, onboarding and off-boarding. Instead of IT building these business-user focused solutions on top of an MDM foundation, vendors are starting to build ready-to-use MDM solutions like the Total Supplier Relationship solution.” Read more about Valspar’s raw materials spend management use case.
5. Increased adoption of matching and linking capabilities on Hadoop
“Many of our customers have significantly increased the amount of data they want to master,” says Dennis Moore. Days when tens of millions of master records were a lot are long gone and having hundreds of millions of master records and billions of source records is becoming almost common. An increasing number of master data sources –internal and external to organization – are contributing significantly to the rise in data volumes. To accommodate these increasing volumes, Dennis predicts that large enterprises will look at running complex matching and linking capabilities on Hadoop – a cost effective and flexible way to analyze large amount of data.
6. Master insight management is going to be next big step
“MDM will evolve into master insight management as organizations try to relate trusted data they created in MDM with transactional and social interaction data,” said Rob Karel – VP of Product Strategy and Product Marketing, IQS, Informatica. “The innovations in machine and deep learning techniques will help organizations such as healthcare prescribe next best treatment based on history of patients, retailers suggest best offers based on customer interest and behavior, public sector companies will see big steps in social services, etc.”
Rob sees MDM at the heart of this innovation bringing together relevant information about multiple master entities and acting as a core system for insight management innovations.
7. MDM and Data Governance
Aaron Zornes – Chief research officer at the MDM Institute predicts that in 2014-15, vendor MDM solutions will move from “passive-aggressive” mode to “proactive” data governance mode. Data governance for MDM will move beyond simple stewardship to convergence of task management, workflow, policy management and enforcement according to Aaron.
8. The market will solidify for cloud based MDM adoption
Aaron says – “Cloud-innate services for DQ and DG will be more prevalent; however, enterprise MDM will remain on premise with increasing integration to cloud applications in 2015.
Naveen sees lot of synergy around cloud based MDM offerings and says – “The market is solidifying for MDM on cloud but the flood gates are yet to open”. Naveen does not see any reason why MDM market will not go to cloud and gives the example of CRM which was at similar junction before Saleforce came into play. Naveen sees similar shift for MDM and says – “The fears companies have about their data security on cloud is eventually going to fade. If you look closely at any of the recent breaches, these all involved hacks into company networks and not into cloud provider networks. The fact that cloud service providers spend more dollars on data security than any one company can spend on their on-premise security layer will be a major factor affecting the transition”. Naveen sees that big players in MDM will include cloud offerings as part of their toolkit in coming years.
Ravi also predicts an increase in cloud adoption for MDM in future as the concern for placing master data in the cloud becomes less with maximum security provided by cloud vendors.
So, what do you predict? I would love to hear your opinions and comments.