Data Management & Analytics

  • blogs
    May 27, 2015

    State of the Hadoop Market

    In this ESG Video Blog, I discuss the current and future state of the Hadoop market.

  • esg tech truths
    May 26, 2015

    ESG TechTruth: Retailers Most Likely to Give Precedence to 'Big Data' Spending in 2015

    In addition to being the vertical with the healthiest overall IT spending change outlook for 2015, retail organizations are more likely than their industry counterparts to prioritize investments in key technology areas, including “big data.” Indeed, ESG’s research reveals that 89% of retailers will increase their spending on BI/analytics solutions relative to 2014 compared with only 57% of the organizations in all other industries.  


  • lab reports
    May 15, 2015

    ESG Lab Review: End-to-end Big Data Discovery with Platfora

    This ESG Lab review documents hands-on testing of the Platfora Big Data Discovery Platform. Testing focused on the simplicity, flexibility, efficiency, and feasibility of deploying Platfora’s modern Hadoop-based big data discovery platform to empower all big data analytics personnel to gain more valuable insights faster.

  • research reports
    May 15, 2015

    Remote Office/Branch Office Technology Trends

    In order to determine the IT priorities and challenges when it comes to supporting the technology requirements of remote office/branch office (ROBO) locations, and how organizations plan to address those challenges, ESG recently surveyed 347 North American senior IT professionals representing midmarket (100 to 999 employees) and enterprise-class (1,000 employees or more) organizations. All respondents worked at headquarters locations or other centralized corporate sites and were responsible for ROBO IT operations and/or strategy, including the delivery of IT services to these locations, authorization of expenditures, and establishment and enforcement of corporate IT policies for remote/branch offices. Respondent organizations were required to have at least two ROBO locations to qualify for the survey.

  • blogs
    May 15, 2015

    Data Analytics for Everyone at IBM Edge

    We live in an unsettling time for enterprise storage technology. It may not be too much of a stretch to say that the future of storage technology is more uncertain now than it has been in the past 10 or 15 years. Emerging technology trends such as the cloud and big data analytics, along with the storage innovations of software-defined storage (SDS) and solid-state are transforming the information technology landscape as we speak.

  • blogs
    May 14, 2015

    Microsoft Invites You to Spark IT Up

    Who builds the world’s most popular tool for analyzing data? Did you say Microsoft? Good. For most anyone in business, Microsoft Excel is where we get started around business intelligence, though we may not typically call it that. From this humble beginning, many graduate on too much more sophisticated solutions. What not everyone realizes is that Microsoft is capable of supporting you even as you go to much greater depth. At the recent Ignite event in Chicago, Microsoft made the case that day will improve worker productivity, especially around data insights and collaboration, with an extremely deep portfolio of complementary technologies.

  • blogs
    May 14, 2015

    The Great In-Memory Database Debate

    Recently the Hive hosted a panel discussion on the pros and cons of various approaches to in-memory databases. Yours truly served as moderator/referee as Oracle, MemSQL, IBM, Aerospike, and Pivotal sent their biggest brains.

  • blogs
    May 13, 2015

    When you think of Hitachi...

    When you think of Hitachi, what’s the first word that pops into your head? Was your word "manufacturing "? Me too. When you think of HDS, what’s your first word? Was it “storage”? Well maybe we need to think again.
  • blogs
    May 12, 2015

    Informatica Grows Up and Gets Organized

    What could possibly entice me to return to Las Vegas for the third time in three weeks? Informatica World 2015. Frankly, I was curious to see just what was a-goin' on with the company. We know this is a group with serious chops in the data management space, but it's also a bit of an anomaly generation-wise. Founded in 1993, Informatica doesn't have so many decades of seniority as IBM, HP, or Oracle, but it's far too old to be a precocious startup any longer.

  • blogs
    May 8, 2015

    Hitachi is Connecting Its Own Dots (Includes Video)

    At the recent HDS Connect Event there were -literally- all sorts of connections to be made. HDS had pulled its sales and partner conferences together with the analyst event, a leadership meeting, and sundry others. The first connection was to parade the huge range of mothership Hitachi's capabilities, and thereby give some tangible credibility to the vision, and even gradual manifestation, of the overall Hitachi drive for "Social Innovation."

  • research reports
    Apr 29, 2015

    Platform-as-a-service Usage and Satisfaction Study

    In order to understand organizations’ usage of or interest in platform-as-a-service solutions, ESG recently surveyed 326 IT professionals and application developers representing small (50 to 99 employees), midmarket (100 to 999 employees), and enterprise-class (1,000 employees or more) organizations in North America. All respondents were personally responsible for evaluating and/or selecting software application development and deployment tools for their organization.

  • briefs
    Apr 23, 2015

    2015 ‘Big Data’ Spending Trends

    A majority of organizations plan to increase spending on the applications, services, and infrastructure underlying big data initiatives, especially those larger in size and affiliated with the retail and health care verticals. This may be attributable to the fact that not only are many organizations that have been experimenting with big data pilot projects now moving into full-scale enterprise deployments, but also those more conservative organizations that have been waiting for more market maturity are now confident enough to proceed with their own initiatives.

  • blogs
    Apr 22, 2015

    Leaders' Perspectives on Big Data: Economic Value

    Previously in this blog series we looked at business and technology goals for big data and analytics initiatives as described by the leaders of these projects at a wide variety of businesses today. The aim is to understand the state of the market and how people seek to drive value from the data naturally occurring in their businesses. While some organizations are truly on the cutting edge, others are taking a more conservative approach or are just now implementing new solutions. Today I’d like to look at some of the ways people actually measure the value of big data and analytics to their business.

  • blogs
    Apr 17, 2015

    Leaders' Perspectives on Big Data: Technology Goals

    I recently started a blog series based on research done by interviewing a number of leaders for big data and analytics initiatives. The first part in that blog series on leaders' perspectives on big data was specifically about business goals. This time we’re going to look a little more at the more technical objectives of big data, by which I mean technology goals.

  • blogs
    Apr 14, 2015

    The Hollywood Perils of Big Data and Personal Information

    I recently saw a low-budget documentary about the perils of big data when applied too broadly to consumer mobile device data. The filmmakers emphasized that when data collection is expanded to include applications like widespread video and audio analysis, significant thought must be given to governance and strict definition of appropriate use cases. Un-authorized access to this real-time information stream could easily lead to personally identifiable information (PII) being used for choosing a particular member of a specific demographic and plotting the individual’s geographic paths, even intercepting them with targeted payloads at vulnerable moments. All without the knowledge or consent of the citizen.
  • blogs
    Apr 9, 2015

    The New Sexiest Job in IT: Data Steward

    For several years, there has been a tremendous demand for data scientists. Businesses and governments got really, really excited about all the possibilities from applying big data, and the data scientist was seen as the most critical role to make it happen.

  • blogs
    Apr 2, 2015

    The Virtual Workload Silo-ization Syndrome (The Webscale Imperative)

    Many data center environments are plagued today by what I’ll call virtualized “silo-tary confinement.” This means that virtualized application workloads are often segregated or containerized within discrete pools of compute, storage, and network resources. For example, a virtual desktop environment may be configured with server, SAN/NAS storage, and networking hardware, while an Exchange infrastructure may utilize a totally separate pool of virtualized resources.
  • esg tech truths
    Apr 1, 2015

    ESG TechTruth: Total Year-over-year IT Spending Change, 2013-2015

    IT spending optimism is at a three-year high, with more than half (56%) of the senior IT decision makers surveyed by ESG reporting that their organizations’ total investments in IT products, staffing, and services will grow in 2015, relative to 2014 budget levels. This equates to an average year-over-year increase of 2.82%, which jumps to nearly 6% among those with plans to boost spending. It is worth noting that only 5% anticipated a drop-off in the funds earmarked for 2015 technology purchases and projects.

  • blogs
    Mar 30, 2015

    Leaders' Perspectives on Big Data Initiatives: Business Goals

    Big data continues to fascinate business leaders across all industries. Yet few agree on a standard definition, much less a best approach to capitalize on the new opportunities and how to leverage new technologies. To better understand the differing perspectives, ESG undertook a series of in-depth interviews with the self-proclaimed leaders of big data initiatives at ten different companies. The goal was to establish a baseline of the most common strategies, as well as identify the philosophical and environmental differences that lead to more distinctive efforts.

  • blogs
    Mar 26, 2015

    Big Data Deployment Models: Open v. Proprietary, Commodity v. Built

    In an earlier blog post, I discussed some architectural options in deploying a big data environment, including cloud vs. on-premises, and dedicated vs. shared infrastructure. In this post, I'll examine topics that may be even more divisive: open vs. proprietary software and commodity vs. purpose-built hardware. These choices seem to reflect personal philosophies as much as technological differences.

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