Microsoft Opens up Its Business Intelligence

Loraine Lawson
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Top 10 Best Practices for Data Integration

Use these guidelines to help you achieve more modern, high-value and diverse uses of DI tools and techniques.

"I believe that data quality will be found in the cloud," data quality and MDM expert Henrik Liliendahl Srensen wrote back in 2010. Somebody give that man a fortune cookie because, sure enough, data quality is coming not just to the cloud - but from the cloud.

 

Last year, integration companies started to couple data quality capabilities with their cloud solutions. It's important for business leaders to understand, however, that "data quality" meant things like deduplication or ways to ensure the data from this spreadsheet corresponds to the data from that spreadsheet - in other words, it tends to mean something very different than what business users would probably assume the phrase "data quality" would mean.

 

But lately, I've seen another option for improving data quality, one more in line with what I suspect business users mean when they talk about data quality. Data integration vendors are starting to add data services to their cloud offerings. These data services improve and correct your data by verifying addresses, phone numbers and even run checks against the do-not-call registry. In other words, they actually improve the quality of your data in a way business leaders will certainly appreciate.

 


Of course, these types of services have been around for some time. (Microsoft's Azure Marketplace has a list of such data quality providers for its cloud offerings and SQL Server, to give you an idea.)

 

So what's new? Data-as-a-service companies are partnering with cloud-based integration solutions to bring these tools to a wider market. Specifically:

 

"Cloud-based computing is radically changing the way organizations approach data management," expressor co-founder and CEO Bob Potter said in the press release. "Our partnership with Melissa Data has been in the works for several months and now together our joint solution will enable companies to take advantage of Melissa Data's cloud-based data verification and enrichment services to build accurate, business ready applications regardless of where the data lives."

 

StrikeIron, which uses Web services to offer its data-as-a-service solution, already had similar partnerships with Salesforce.com, as well as Eloqua, Magento and Oracle CRM On-Demand.

 

But there are benefits to placing the data cleansing and verification with integration, whether you're working with data on-premise or in the cloud.

 

"Informatica Cloud ensures that our Salesforce CRM users never need to leave the platform," Laura McKevitt, CRM Manager, CETCO, is quoted as saying in a press release. "Broadening cloud-based connectivity and a continued focus on simplicity and ease of use will make the Informatica Cloud Winter 2012 release an

even more critical component of our IT infrastructure."

 

StrikeIron seems to be at the forefront of this embedded data-as-a-service solution: It recently won the Cloud Infrastructure and Cloud Computing Company of the Year awards in the inaugural 2012 Cloud Awards Program. It was also nominated in the Data Innovation of the Year category.

 

This sort of data offering could make the cloud even more attractive to small and mid-size businesses.

 

Right now, the offerings mostly center around correcting customer data, which is great for CRM systems. But there are also more intriguing possibilities - for instance, there are data services that could be used to integrate geospatial data.

 

Srensen predicted two years ago that the Internet could be a tremendous aid to resolving data quality problems.

 

"Many of the data quality issues I encounter in my daily work with clients and partners is caused by that adequate information isn't available at data entry - or isn't exploited," Srensen said. "But information needed will in most cases already exist somewhere in the cloud. The challenge ahead is how to integrate available information in the cloud into business processes."

 

Coupling data quality with integration seems like a smart way to "address" that problem.



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Resource centers

Business Intelligence

Business performance information for strategic and operational decision-making

SOA

SOA uses interoperable services grouped around business processes to ease data integration

Data Warehousing

Data warehousing helps companies make sense of their operational data


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