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How Will the Increased Use of BI Affect the Traditional Data Center?

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David Linthicum: How will the increased use of BI affect the traditional data center?

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  • Broader adoption of BI across the business implies that:
    - the ease-of-use must be such that non-technical users can easily view, interact with and analyze information that is relevant to them;
    - consistency of data becomes even more important since everyone across the organization should base decisions on a "single version of the truth";
    - context and collaboration are critical to understanding and so ensuring users have an easy way to view a definition of the data, the formula used to calculate metrics etc, and the ability to share knowledge with others helps their level of understanding.

    Some of these requirements can certainly be delivered out of the traditional data center, however for innovation in user interfaces, analytic capabilities and delivery methods, new software models and solutions should be explored.

    IT and the traditional data center must evolve and build on their core competency and remaining the data custodians ensuring consistent, clean, accurate data is available for use across the organization. Leveraging SaaS solutions to rapidly deliver against business requirements makes sense since business demands are greater than ever while budgets continue to be very tight. Complementing internal BI capabilities with externally delivered operational BI can expand user adoption, deliver the necessary usability and functionality, and makes particularly sense where data spans multiple companies for example in a multi-company supply chain.

    IT still has an important place to play as a service broker ensuring the external solution meets functionality, security and service level requirements.

  • How will the increased number of eggs affect the chicken?

    Traditional data centers focus on traditional IT initiatives and so this is really a "chicken-or-egg" question. The increased use of BI will have to come from somewhere else. My bet is that it will be delivered by Cloud BI projects directly to the business users. And as more and more apps will be delivered as service the traditional data center will become more and more "legacy" data center...

    Roman Stanek
    CEO, GoodData

  • The concept of a data center is fast becoming obsolete. Either a lot of BI is already done locally on many Skunkworks projects even with a central data warehouse and reports that many ingore!

    In addition to this data centers are clouds that you have no idea where they are physically. BI will also be collecting and storing data in the cloud with the BI analysis services accessing it without knowing where they are physically.

    The concept of Data Center is fast becoming one of a virtual existence!

  • From an enterprise standpoint, Data Centers are synonymous to Business continuity and Data Security. Data Center helps manage the IT platform(s) and provide support for applications that run on top of it. With or without BI, Data Centers will continue to be an important part of IT in any organization.

    BI for Data Centers can emerge as a solution to improve Data Center management. For example, predictive analytics around outages, concurrent usage, bandwith utilization, etc. can help manage the enterprise IT needs in a better manner. With more cloud based applications, a data center for a specific organization has to deal not only with on-premise data but also with data on the cloud. Bottomline - as far as Business continuity and Data Security is concerned, the buck stops with the Data Center and that is not going to change.

  • The Data Center is not going to disappear anytime soon. However, cloud offerings from a number of vendors including Amazon, Microsoft and Google are beginning to supplement the data center on a number of fronts, and these include business intelligence and analytic solutions. And, as demand for dynamic analysis increases, new emerging startups like Cloudswitch are helping organizations easily migrate applications back and forth between data centers and cloud platforms. This is a very exciting development in the market. But several key challenges remain when it comes to business intelligence and analytics:

    - Heavy increases in both the sources and volume of data, which will require that organizations find new ways to address data center storage and the associated costs. One way this can happen is through the adoption of databases that include deep compression of the core data.

    - Performance, performance, performance. As BI continues to be a strategic imperative, the data center will face pressure to reduce the latency involved in getting bottom line business analytics and reports delivered to decision makers. To speed things like query performance, data centers can take advantage of a new generation of servers that will contain chips like the future Intel Single-Chip Cloud Computer. According to Intel, this microprocessor will enable the most cores ever to fit on a silicon chip—48 cores and can scale to over 100 cores . Data centers will also increasingly adopt columnar databases. Now considered mainstream, columnar configurations help to further reduce the latency in data delivery for business intelligence, analytics solutions and other applications.

    - Power Consumption. As data volumes increase by gigabytes daily, the traditional response has been to throw hardware at the problem, including more powerful servers and more of them. The result is a massive infrastructure footprint, with massive space, resource, maintenance and energy requirements. While the IT industry has begun to address the problem of energy consumption in the data center through a variety of approaches, including the use of more efficient cooling systems, blade servers and virtualization, organizations also need to start looking at how to minimize the amount of space and resources that their data take up in the first place ― a challenge that is beginning to be tackled with the help of open source technologies.

  • I agree with Wayne that ease of use, consistency and context are becoming increasingly important factors. Most companies aren’t using the data center for all of their BI needs (if they ever did); and many companies, especially SMBs, don't need a data center for their BI needs at all. However, just because the data center may see waning usage as the center of the BI universe, SaaS and cloud-based BI are not a panacea. Plenty of “in-house? software BI solutions, such as in-memory or report mining, offer powerful, yet inexpensive and end user friendly BI. The insight they provide is not tied to the data center, and they also don’t require accessing and moving data into the clouds with its attendant security risks and integration issues. The common thread here is that BI is becoming more pervasive and more accessible to the end user without the need for long implementation and training cycles. Ultimately, this allows those who need BI most to set it up quickly and use it effectively.

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