In an environment where lack of trust is common, the data warehouse challenge is not just finding the best warehouse technology, but also determining how to create a warehouse that instills confidence among the business users who receive the output of analysis.
Andy Hayler, CEO of The Information Difference, tells us that “the average large company has six different competing sources of customer data and nine different competing sources of product data.” For companies to succeed data quality is imperative.
Confidently make decisions with IBM Big Data
In the world of big data, the elephant is king. Hadoop, whose elephant logo has become the face of big data, has been joined in the big data jungle by many friends: Pig, Jaql and even a ZooKeeper to keep them all in line. The entire big data jungle will be making a trip to Las Vegas in October for
This infographic touches on five critical steps that will help customers streamline their application infrastructure, reduce infrastructure costs and transform enterprise data into a trusted, high-value resource by successfully consolidating and retiring their applications.
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Big data does not make data quality redundant. As long as there is a need to make sound decisions based on information and insights, there will be a need for data quality and governance. Data quality function will adapt to the changing business needs and play a crucial role in building confidence
When people say about some found object, "don't touch it, you don't know where it's been," they might as well being speaking of data. You can't use any data with confidence until you ascertain where it came from, who handled it and what they did with it.
The promise of big data and analytics is revolutionary and exciting. But, to truly make big data a big deal requires confidence in your data. Learn how two teams tried to use analytics to fund a an enterprise project with dramatically different results. Discover how one went wrong and how the other
For a business person who has struggled to take responsible action based on questionable data, there is something immensely energizing about the arrival of information that is clear, relevant and well founded. Even if the data brings bad news, the facts themselves provide a level of confidence so
Twice recently, in two different large companies, people whom I have otherwise respected as being quite sensible have said to me that their organisations had appointed people who, within their own function, were ‘responsible for data quality’.
Well, when I went to Data Governance School back at the
At a recent IBM event focused on building confidence in big data, a highlight was a wide-ranging discussion by a panel with very diverse backgrounds and industries. The panel comprised an industry analyst with an information governance specialty (Michele Goetz of Forrester Research), a chief data
"Anyone who makes assertions and is unwilling to engage in a discussion or provide evidence for what they say, is probably someone who doesn't really know what they're talking about. Be very skeptical."
That's the advice from Tom Deutsch, program director of big data and analytics at IBM. In this
Businesses are plunging headlong into the age of social listening analytics without fully thinking through the many issues surrounding the quality of this intelligence. There is plenty of valuable customer intelligence to be had from filtering the social firehose. However, the overwhelming volume,
Meet Mr. Confident and Mr. Not-So-Sure. Both are living in a big data world, but only Mr. Confident is succeeding. Mr. Not-So-Sure struggles with understanding the context, completeness and risk associated with data. On the other hand, Mr. Confident utilizes trusted insights from the growing volume