Category Archives: Data Services
If data is an asset, why should you give it away? Open data is based on the notion that some data should be freely available to everyone to use, similar to other “Open” movements such as open source software. But open data doesn’t have to only be about exposing information publicly; the same concepts can be applied inside your firewall. Here are a few examples: (more…)
Those moving to Big Data, and that is a lot of enterprises right now, should also consider the need for data integration to support their new data platform. In many cases, the use of proper data integration procedures and technology is an afterthought. However, with a bit of planning and the right data integration technology, the transition to Big Data can be a smooth and productive one. Here are a few things to consider:
Data quality becomes even more important. Considering that Big Data systems, no matter if they are within the cloud or the data center, manage massive amounts of data, both structured and unstructured. Thus, the ability to manage data quality becomes more of a priority. (more…)
Apparently, everyone’s favorites words these days are “big data.” But just because some new tools and techniques promise the potential of absorbing and analyzing huge amounts of data from a variety of sources, it does not mean that installing Hadoop in your enterprise is going to automatically help you to get new insights from existing and “big data,” faster. (more…)
Sometimes when you want to sell SOA, you need to sell the concept and not the buzzword. Case in point, when I speak at a conference. If I talk about SOA patterns as a way to drive to a better architecture, I often see eyes begin to roll. However, if I say we’re looking to externalize services that will be meshed and re-meshed together to form business solutions, thus providing agility…the eyes light up. Funny thing is, I’m talking about the same thing. (more…)
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. (more…)
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 (more…)
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. (more…)
If you’re reading this article, you’re probably interested in big data, but don’t really know what you’re looking for with big data or how you’ll find it. Don’t feel confused. It’s not like traditional analytics, where you know the structure of the data – the relations across sources, the dimensions to build, the calculations to perform – and the reports you need. Big data can be completely unstructured, with no clear relationships. And you don’t know what you’re looking for until you find patterns. A complaint might come in about an online shopping cart being wiped out, which is what happened to my wife with a big toy retailer during some online Christmas shopping. I’ll tell you right now they ended up losing a lot of money. If they’re using big data, they might find a pattern of the steps that made her hit that bug. Then they might search for all customers that had the same problem, get their e-mail addresses or names, and do a recovery campaign. I hope the retailer is using big data properly. My wife would receive a call, and get that order. They’d be happy, and I’d be happy.
The “Dodd-Frank Wall Street Reform and Consumer Protection Act” has recently been passed by the US federal government to regulate financial institutions. Per this legislation, there will be more “watchdog” agencies that will be auditing banks, lending and investment institutions to ensure compliance. As an example, there will be an Office of Financial Research within the Federal Treasury responsible for collecting and analyzing data. This legislation brings with it a higher risk of fines for non-compliance. (more…)