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  • single source of truth (SSOT)

    Single source of truth (SSOT) is a concept that an organization can apply as part of its information architecture to ensure that everyone in the organization uses the same data when making business decisions. The aim of adopting a SSOT is to provide employees with a federated view of data, which may also be referred to as a single version of the truth or golden record. Continue Reading

  • passenger name record (PNR)

    A passenger name record (PNR) is a collection of data pertaining to an individual air traveler or a group of individuals travelling together. Airlines use PNRs for management of customer data, security and customer valuation and may share that data with government agencies. Continue Reading

  • Monetizing customer usage data

    IoT creates a plethora of customer usage data; but how can it be monetized? Explore key factors to keep in mind when deploying a data monetization engine. Continue Reading

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  • Data governance programs loom larger than ever in the big data era

    Big data, when managed properly, can be a blessing to businesses fighting to gain greater insights and a competitive edge in the global marketplace. And it can be a curse to companies unprepared to handle the untold x-bytes of unstructured data unceasingly pouring into their coffers. That's the dilemma most organizations wake up to each day, and as a result, they capture only a fraction of the value that big data analytics promises. At no time is there greater urgency for companies to establish data handling policies and procedures that only good data governance programs can provide.

    June's Business Information opens with a stern warning in our editor's note: Don't wait till it's too late to initiate a data governance program. Big data governance can be a highly complex process. Its tentacles reach into most aspects of data management, from data gathering, integration and preparation to quality control. Even more difficult is securing the cooperation of a potentially reluctant and resistant workforce intimidated by thoughts of a data police force regulating and scrutinizing their work. For those reasons, most companies have taken the path of least resistance and avoided setting up formal and reliable data governance programs -- much to their own peril.

    Our cover story then stresses the importance of establishing data governance policies dedicated to placing customers first. The lack of such rules has led to customer privacy violations, millions of lost dollars in legal settlements and famous brands nearly destroyed. Data governance provides the necessary checks and balances that help companies adhere to responsible behavior when they probe into the minds and habits of their customers. In our feature, we examine companies that have taken on the challenge of governing their vast data lakes by piecing together various governance tools and mechanisms in do-it-yourself fashion. And we devote numerous more features and columns to help companies apply data governance principles in ways that can bring order to chaotic big data environments.

    Also in this issue, see how a small wine shop uses ready-made big data analytics to outsmart much larger stores as they all compete in the same neighborhood for the same customers.

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  • Don't wait until it's too late to build a data governance model

    As companies amass data from multiple sources, they lose control over data quality and accuracy. Like it or not, it's time to halt the data free-for-all and apply data governance. Continue Reading

  • Finding the way to different types of databases, big data tools

    In a Q&A, EMA analyst John Myers advises IT teams to look at big data workloads when sorting through new and different types of databases and open source tools. His word on Spark? It's still young. Continue Reading

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  • VMware uses machine learning algorithms for proactive problem solving

    Machine learning requires massive amounts of data to identify issues before they occur. VMware uses Skyline proactive support technology to more efficiently farm that data. Continue Reading

  • Ignore customer data quality at your peril

    Customer data management is not high on many organizations' lists of priorities -- until it has to be. Customers get the same ads over and over again. They say a company they've done business with for years doesn't know them. Or thinks they're someone else. Then they get mad. Then they leave.

    Sound familiar? It should, because it's all too common. This issue of Business Information explores customer data quality issues at Boston public media organization WGBH, which hadn't kept its contact data stores clean for 60 years. The result was a morass of disorganized, incorrect and duplicate data that did little to impress donors that keep WGBH's TV and radio broadcasts on the air. In their cover story, Lauren Horwitz, executive editor of SearchCRM, and Tim Ehrens, site editor, look at the customer data messes made at WGBH and other organizations -- and how they remedied, or are remedying, the problems. Sophisticated technology like master data management software is one possible solution to the problem, Horwitz finds -- and good, old-fashioned data cleansing is another. Continuing the focus on customer data, Ed Burns, site and news editor of SearchBusinessAnalytics, reports on the customer analytics programs at companies such as eBay, Sears and Netflix. They're tapping their vast wells of customer data to extract valuable insights that can aid efforts to both attract new customers and keep the ones they already have happy.

    Grab another cup of joe and keep reading for a reality check on Java 8, the newest version of the programming language. Oracle released it in March and says its language structure is simpler, making it easier than ever to design software. But does it stand up to rival languages like Scala and Clojure -- and will big organizations even opt for Java 8 when they can extend investments in older versions?

    There's more: Dreamforce 2014 attendees' take on Salesforce.com's new analytics offering, a human resources IT director originally from Vietnam whose difficult assimilation to the U.S. led her to improve the new-hire orientation process at her current employer, and a new writer of our "Connect IT" column tells readers to throw out everything they know about the software selection process.

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  • Poor customer data management equals poor customer experience

    When companies abuse customer data, they abuse the customer relationship. Manage customer data as carefully as you would your own corporate data. Continue Reading

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