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  • Managing the big data ecosystem requires agility amid disruptions

    In some regards, the term big data management can be viewed as an oxymoron. In fact, oxymorons abound in this industry and society -- virtual reality, artificial intelligence, science fiction and awfully good, the latter of which can apply to the challenges encountered in managing the onslaught of big data from multiple sources. There are countless tools, techniques and practices available for the big data ecosystem to properly gather, mine, prep, store and analyze data and help smooth operations, build marketing campaigns, improve customer service and develop the next new product disruptor. As simplistic as this may sound, it's up to data managers to sort it all out as their data lakes swell beyond capacity.

    "The data lake isn't where data goes to die," Gartner analyst Merv Adrian said at the 2017 Pacific Northwest BI Summit, "it's where data goes to live."

    October's Business Information opens with our editor's note and advice for data managers to move beyond traditional data control to the critical task of improving data quality and delivery -- taking all that raw data and making it useful. Whether for internal or external business use, the demands for instantaneous data access continue to accelerate, spurred on by mobile apps, artificial intelligence (AI), machine learning and internet of things (IoT).

    In that vein, our cover story examines companies that use their big data ecosystem to divert data lakes toward developing new strategies, products and revenue streams -- in the process, smashing their old business patterns. In another feature, IoT and machine learning technologies help take the guesswork out of estimated times of arrival for transport companies whose businesses depend on shipping and receiving goods.

    Also in this issue, a business intelligence project combined three data warehouses into one to reduce warehouse size by 80% and data load time from several weeks to just days while causing IT staffing problems in the process. In other features, learn how metadata programs can ease mega management woes; semantic technology could be a blessing or curse to AI; companies are gearing up for greater big data management deployments; and all data must be treated equally in the search to find value.

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  • A strong metadata management process eases big data woes

    Big data often comes with big data management problems. Clean, well-defined metadata can make the difference in analyzing big data and delivering actionable business intelligence.Continue Reading

  • What to look for in web content management software

    Content management systems can help an organization support the entire content creation process, from production to delivery -- but there's much to consider in WCM systems.Continue Reading

  • DriveCleanup Clears Stale Win10 Storage Metadata

    Uwe Sieber's excellent tool DriveCleanup clears stale Win10 storage metadata, so Device Manager shows what's present on your PC, and no more.Continue Reading

  • Mixed metadata, master data management process a must for mobile apps

    The growing use of mobile devices by business users broadens the risk of data inconsistencies, a hazard that an integrated process for managing metadata and master data can help address.Continue Reading

  • Q&A: Big data leads to bad insights without a data governance plan

    Big data holds the potential to provide invaluable insights for business growth, but only if data governance is part of the plan.Continue Reading

  • How does deduplication in cloud computing work and is it beneficial?

    The deduplication process reduces the amount of data in a storage system, but dedupe in the cloud may be more valuable to the cloud provider than the customer.Continue Reading

  • Staring down the security issues in cloud computing

    Adoption of cloud computing has no doubt been slowed by worries about the security of those out-of-sight servers and resources. While reasonable, those worries have given way over time to acceptance and even optimism.

    In this month's Modern Infrastructure cover story, TechTarget’s Trevor Jones writes about why security issues in cloud computing are not the impediment to adoption that they once were. In fact, some organizations are coming to the conclusion that their workloads run more securely in a public cloud than in an on-premises environment. Cloud service providers possess security expertise and experience at levels that aren’t as readily available on a typical IT staff, and certifications give confidence that providers can actually do all they claim to do.

    The public cloud is not a risky place to do business, though its safeguards are different from those you've put in place to protect your own data center. These differences are most clearly seen when looking at the shared-responsibility model, which addresses many of the security issues in cloud computing. Users and providers must each do their part. Otherwise, the risks will become apparent, and cloud computing won't be what you need it to be.

    This issue also looks at how a new wave of products in development brings memory and storage technologies closer together. Nonvolatile dual-inline memory modules, for example, combine the speed of memory with the persistent qualities of storage in some interesting ways. Also included is an article on how some IT shops that have adopted flash storage are simultaneously impressed and disappointed with the results. Costly flash products invariably improve performance, but they won't solve every problem or clear every bottleneck.

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  • Internet of things data security proves vital in digitized world

    Securing IoT data should become a priority as more companies manipulate the volumes produced by these devices. Seemingly innocuous information could allow privacy invasions.Continue Reading

  • Metadata management tools help data lake users stay on course

    Effective metadata management processes can prevent analytics teams working in data lakes from creating inconsistencies that skew the results of big data analytics applications.Continue Reading

  • BI self-service needs new thinking to truly serve business users

    To be truly useful to a broad set of business users, self-service BI tools need to become easier to use. An increased focus on metadata and artificial intelligence can help with that.Continue Reading

  • Update your data backup policy with new options

    The server backup market first evolved to protect VMs, but now it's undergoing another transformation. Find out how it's evolved and what you need to know for the future.Continue Reading

  • Smart storage systems smart for business

    Mike Matchett explains how data-aware storage combined with application awareness is leading to a new wave of intelligent data storage.Continue Reading

  • Metadata injection marks Pentaho big data pipeline

    The crush of big data leads some data pros to seek more automation of data integration processes. The Pentaho software platform now offers metadata injection capabilities to help meet such needs.Continue Reading

  • Push your digital asset management strategy beyond metadata

    Digital asset management needs to go beyond metadata to build and maintain branded digital experiences that include mobile and rich media. An expert offers tips on how to begin.Continue Reading

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