One of the big obstacles to implementing advanced data analytics in the enterprise is how complex it can be. Whether you were starting with business intelligence a decade or more ago, or are trying to build a data science practice today, enterprises often cite the complexity of putting together the resources and technology to make it all happen. Analysts have often urged starting with small, high-impact projects to get to a quick win. From there it can be easier to get the investment dollars to expand the technology throughout the organization.
But the challenge remains in a lot of cases. Enterprises may find themselves experimenting with multiple technologies and spending more time creating the platform than doing the analytics. Sensing the opportunity, vendors have been working to make it easier on analytics champions inside the enterprise. From cloud offerings such as Amazon’s AWS and Microsoft’s Azure to big data platform providers such as Cloudera, Databricks, Hortonworks, and MapR, there’s a host of vendors offering platforms that let you consume the services you need with prices based on consumption rather than a big capital investment in infrastructure.
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