Today, an application without data analytics is like a car without a steering wheel. It will go, but there’s no controlling its direction.
The cloud and big data are infiltrating company practices, and in some cases, they’re doing it together. The intersection of the two brings many challenges and opportunities for companies that choose to process and store big data in the cloud. Once companies decide to host big data in the cloud, they’ll want to assess their circumstances and decide what works best for them.
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Nowadays, there are many emerging and evolving Web- and cloud-based technologies for controlling and using data inside applications, and they’re available as full-featured cloud suites, the popular Hadoop programming framework and other business intelligence tools that can be embedded into applications.
Recently, the SearchCloudApps team wrote a series of articles that looks at different platforms and tools developers can use to harness big data in the cloud. Here’s the lowdown on the advice, tips and information this series offers, both in our special report and supporting advice articles on SearchCloudApps.
First off, SCA News Writer Joel Shore shares advice on how software pros can use big data as a service (BDaaS) in the lead story of our special report, Pick the right tools for cloud and big data. BDaaS delivers a platform and suite of tools that can speed up builds of analytics applications. The article describes how BDaaS expands the capabilities of cloud-based analytics.
Is BDaaS the right data analytics development platform for your organization? CIMI Corp. CEO and cloud consultant Tom Nolle answers that question in the series’ second story, How to choose the best cloud big data platform. He describes and opines on BDaaS (big data as a service) and do-it-yourself options and covers the role databases play. He notes that “cloud planners need to decide on a database model, select between cloud database services and cloud database platforms, and review the features of each platform against their own special needs.”
Nolle questions a key big data tool assumption, that Hadoop fits all situations, in his tip. Cloud and big data don’t necessarily mean Hadoop. To Hadoop or not to Hadoop, he advises, depends on such variables as whether data access is centralized, the level of data distribution performance needs, database practices and more.
Joel Shore digs deeper into the pros and cons of BDaaS in his new report, Beware of the BDaaS double boomerang. What does that mean? Essentially, as data volume grows, there can be conflicts between IT, which manages data analytics processes, and marketing and other departments who demand more and more access and capabilities. “We often see the marketing and sales departments getting tired of waiting for projects, so they jump over IT and do it themselves,” Enterprise Strategy Group analyst Nike Rouda told Shore. Sounds like trouble in Data City, and that makes interesting reading.
SearchCloudApps coverage of the big data, BDaaS and cloud analytics scenes is ongoing, and our readers help us tailor our reports to your needs. Are you evaluating solutions for embedding data analytics into applications and can’t find the advice you need in these articles? Tell us about your projects, and our editors and resident experts will looks for answers to your problems.