Modernization requires unification
.@philsimon channels his inner Queen Latifa.
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Who was that masked data?
Data access and data privacy are often fundamentally at odds with each other. Organizations want unfettered access to the data describing customers. Meanwhile, customers want their data – especially their personally identifiable information – to remain as private as possible. Organizations need to protect data privacy by only granting data access to authorized
Crowdsourcing data assets in the data lake
A long time ago, I worked for a company that had positioned itself as basically a third-party “data trust” to perform collaborative analytics. The business proposition was to engage different types of organizations whose customer bases overlapped, ingest their data sets, and perform a number of analyses using the accumulated
ETL and data warehouses are dead! Long live ETL and data warehouses!
Why they will still play a valuable role in organizational data-management and -integration efforts.
Hadoop and MDM – Who is the master?
Today, I was in a conversation about using Hadoop (a big data platform) for master data management (MDM). I still find it amazing when we have the discussion of what systems feed another system. Many of our friends have spent years creating MDM for customer, product, etc. with success. I'm a
Modernisation is the new normal
In my last post, I talked about how to observe the impact of modernisation through a data quality lens. I asked you to consider the quality of your legacy data and what that means on the "shiny new toy" you intend to buy in the future. In this post, I
Four DI modernization mistakes
.@philsimon with some recommendations on modernization.
Modernization and data-driven culture – Part 2
Modernization is a term used to describe the necessary evolution of information technologies that organizations rely on to remain competitive in today’s constantly changing business world. New technologies – many designed to better leverage big data – challenge existing data infrastructures and business models. This forces enterprises to modernize their approach to data
Data ops: Better way to prepare data for analytics and IoT?
We all find change easier when it starts with something we’re familiar with. That’s why I think sports analytics examples are popular – most of us are sports fans, so we get it more easily. It’s also why automotive examples that illustrate the potential reach of the Internet of Things
A modernized approach to data lake management
In my last post, I started to look at the use of Hadoop in general and the data lake concept in particular as part of a plan for modernizing the data environment. There are surely benefits to the data lake, especially when it's deployed using a low-cost, scalable hardware platform.