Are you even (nearly) ready for Big Data?

Big Data.  What is it? Those of us who have helped organizations improve competitiveness through more effective use of information know that most data has value. The trick is in defining that value, determining how best to get at it and then executing a process to extract it. Every few years it seems we have to create a rally point for more focus on just how impactful information is, and for the past several that rally point is Big Data. If you believe what you read and hear, it can be pretty much anything you want it to be. But there is at least one shred of truth in what we call it; it is BIG. Read more

This Post Is Not About Big Data

Big Data is clearly the buzzword du jour in the information management space right now. I read a great article by Jim Ericson a few days ago where he talked about the hype around big data and how vendors, consultants and analysts have glommed on to (my word) the term and its pervasiveness in all topics information management. Read more

Don’t Boil the Data Governance Ocean

In a recent blog post, a Forrester analyst suggested that organizations should create a combined program for “information governance” that would cover governing both data and content. The premise is that there should be enough common ground and similarities in the two governance programs such that organizations can create “an information governance framework that will address both their structured and unstructured information [which] requires that the appropriate IT and business roles and responsibilities are clearly defined and that stakeholders from both IT and business are in agreement with the design and implementation efforts for an effective information governance strategy.” Read more

Get it Done, Right, the First Time (or at least from now on)

I recently read a great blog by Aaron Zornes, “Go Governance, Go Early”, in which Aaron called out the need for the discipline of a Master Data Governance to coincide with the deployment of an MDM solution. I couldn’t agree more! Read more

Bad data made me go digital

So, I have to admit it: Like most people, I’m a creature of habit. When I realized I was getting to the end of my trusty National® Brand 150-page lined account book (known to most people as a notebook), I fired up my browser to buy some replacements. Unfortunately, the company where we buy office supplies from carries something similar, but not identical. So I left the confines of our approved suppliers and found my product. I ordered 2, and selected 3-day shipping. Read more

Physics of Information Management: Work Done by a Spring




Previous Post: The Physics of Information Management: The Pendulum

Please Stop Trying to Come Up with a Single Enterprise Definition of Customer

Try this. Think back through all the data warehouse, MDM, BI and other assortment of data management projects that you’ve been involved in. Can you think of a case in which an entire enteprise adopted a single definition of customer? Or a single definition of product? Your project team might have put together a definition. But was the definition widely accepted? Read more

Achieving Fully Governed Master Data

This is my third and final post in my series about what to look for in your master data management solution. The first topic was about modeling your master data, the second was mastering the data, and this one is about governing the master data. Read more

How to be the master of mastering your master data

In my last post, I discussed how important it is to be able to effectively model your master data. In this, the second in a series on the topic of master data, I want to discuss how you need to master it. By “master it,” I am referring to the workflow-driven process steps people go through to achieve clean, consistent, accurate and harmonized master data, and having the relevant technical capabilities to make this process work smoothly and efficiently. And by “people,” I mean everyone involved. Read more

MDM and data quality for the data warehouse

A recent Information Management article raised a number of issues with data warehouses and why they are such time-consuming projects. According to the article, the main reasons are primarily around changing scope, data quality and ETL design. I’ve discussed how to handle the scope and design issues in earlier posts about business modeling. Over the next few posts, I’ll talk about how to deal with data quality in the data warehouse. Read more