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As big data gets bigger, enterprise governance attempts to keep up.

One of the hallmarks of big data is that it is coming from everywhere and anywhere, creating massive headaches for data and IT executives. Data flowing in may have different formats, represent murky timelines, or be of less-than-stellar quality. Such concerns, while valid, actually mean little to business decision makers. They simply expect IT and data management departments to be able to pull all available information resources together and make it highly accessible to the business as actionable insights, automated decisioning systems, or via self-service platforms.

The good news is that some enterprises are gaining a semblance of control over, and are seeing business value from, their big data assets. They are enriching their capabilities through a variety of data governance initiatives. Some companies have more routine, established and comprehensive processes and policies in place, while others have ad hoc approaches to the same challenges. The troubling news is that most organizations are only just beginning to recognize the scope of the challenge that lies ahead of them and are not satisfied with the pace of data integration.

To better understand the impact of new data sources on data governance practices, IBM commissioned Unisphere Research, a division of Information Today, Inc., to survey 304 managers responsible for data management in their organizations. ("Governance Moves Big Data from Hype to Confidence")

The survey finds that organizations are investing heavily in initiatives that will increase the amount of data at their disposal. The survey also finds that the percentage of organizations with big data projects in production is expected to triple in the next 18 months. However, as the amount of data grows, they are spending more time finding needed data rather than analyzing it.

Concurrently, very few companies feel entirely confident about the data that is coming in from all sources, and they are significantly less confident in data gathered through social media and public cloud applications than they are in data generated internally. Internal, structured data evokes the highest level of confidence. (See Figure 1.)

While confidence is an issue overall, managers generally trust reports based on the analysis of big data, even though the data quality may not be as good as that of reports based on traditional, internal data. As data grows within enterprises, analysts may find themselves spending more time defending the quality of their data than ever before. And the problems of security lurk beneath the surface of every conversation about data and data analytics. As companies accumulate more and more sensitive data about their customers, the need to keep that information private and secure is paramount.

To help this process, many executives and professionals say their organizations have embarked on comprehensive data governance programs, intended to ensure data quality, as well as value to the business. Forty-three percent of respondents indicate their organizations have data security and privacy initiatives in place, and another 38% have information integration frameworks. About one-third have data quality initiatives underway.

However, the survey finds that most respondents are not satisfied with the development of their information governance programs. Information governance initiatives often have limited scope, lack business sponsors, and have trouble winning funding when competing with other IT priorities. A total of 44% say their data governance programs are either "immature" or "somewhat immature" compared with only 28% who would consider their programs to be "mature" or "somewhat mature." (See Figure 2.)

Of the information governance projects that have moved forward, data security and privacy are ongoing top-of-the-agenda issues. Most data governance efforts tend to be scattered across enterprises--56% of respondents say that such initiatives tend to arise as standalone projects, or are required as part of another initiatives. Only 25% indicate that their organizations have coordinated, enterprise-wide programs.

The role of data governance is to build confidence that enterprise data used for analysis and in applications can be trusted. Whether they are consolidating and retiring applications to modernize their infrastructures, creating an enhanced 360-degree view of customers, or tackling other data-intensive projects, data and IT managers are competing for budget and resources with other priorities on a list topped by the maintenance of existing applications.

Figure 1: What is Your Confidence Level
in Each of These Data Sources?

                            Confident   Not confident

Structured data in your
internal systems               63%           14%

Data provided by your
business partners              37%           29%

Unstructured data in your
internal systems               21%           44%

Data stored in a public
cloud                          23%           50%

Social media data              13%           61%

Note: The remaining respondents for
each data type had neutral responses
(neither confident nor not confident).

Note: Table made from bar graph.

Figure 2: How Would You Rate Your Organization's
Current Maturity Level?

Immature             18%
Somewhat immature    26%
Neither mature nor
  immature           28%
Somewhat mature      21%
Mature                7%

Note: Table made from bar graph.
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Title Annotation:Research@DBTA
Author:McKendrick, Joe
Publication:Database Trends & Applications
Date:Aug 1, 2014
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