by Rob Meyer on February 6, 2012 – 11:22 am
I just came back from MicroStrategy World. There were many conversations about social, mobile, cloud and big data. There was strong interest in cloud, clear adoption of mobile, and some big data adoption. eHarmony had a great presentation about how they handle big data with Informatica, and how they’re starting to use Hadoop with Informatica HParser running on Hadoop for processing JSON.
But that wasn’t the number one conversation. The one topic that everyone was interested in – and I talked to nearly 100 customers and partners over four days – was creating new reports faster, or Agile BI. Read More »
by Ash Parikh on January 25, 2012 – 7:30 am
Today, agility and timely visibility are critical to the business. No wonder CIO.com, states that business intelligence (BI) will be the top technology priority for CIOs in 2012. However, is your data architecture agile enough to handle these exacting demands?
In his blog Top 10 Business Intelligence Predictions For 2012, Boris Evelson of Forrester Research, Inc., states that traditional BI approaches often fall short for the two following reasons (among many others):
- BI hasn’t fully empowered information workers, who still largely depend on IT
- BI platforms, tools and applications aren’t agile enough Read More »
by Ash Parikh on January 23, 2012 – 10:18 am
If you haven’t already, I think you should read The Forrester Wave™: Data Virtualization, Q1 2012. For several reasons – one, to truly understand the space, and two, to understand the critical capabilities required to be a solution that solves real data integration problems.
At the very outset, let’s clearly define Data Virtualization. Simply put, Data Virtualization is foundational to Data Integration. It enables fast and direct access to the critical data and reports that the business needs and trusts. It is not to be confused with simple, traditional Data Federation. Instead, think of it as a superset which must complement existing data architectures to support BI agility, MDM and SOA. Read More »
by Clarke Patterson on January 20, 2012 – 12:15 am
Following up from my previous post on 2011 reflections, it’s now time to take a look at the year ahead and consider what key trends will likely impact the world of data quality as we know it. As I mentioned in my previous post, we saw continued interest in data quality across all industries and I expect that trend to only continue to pick up steam in 2012. Here are three areas in particular that I foresee will rise to the surface: Read More »
by Clarke Patterson on October 12, 2011 – 2:24 pm
Data quality improvement isn’t really anything new; it’s been around for some time now. Fundamentally the goal of cleansing, standardizing and enriching enterprise data through data quality processes remains the same. What’s different now, however, is that in an increasingly competitive marketplace and in difficult economic times, a complete enterprise data quality management approach can separate the leaders from the laggards. With a sound approach to enterprise data quality management, organizations reap the benefits of turning enterprise data into a key strategic asset. This helps to increase revenue, eliminate costs and reduce risks. Using the right solution, organizations can leverage data in a way never possible before, holistically and proactively, by addressing data quality issues when and where they arise. Doing so ensures key IT initiatives, like business intelligence, master data management, and enterprise applications, deliver on their promises of better business results. Read More »
