- May 22, 2013
Big Data is sweeping the business world – and while it can mean different things to different people, one thing always rings true: data-driven decisions and applications create immense value by utilizing data sources to discover, present, and operationalize important business insights.
While there is broad industry consensus on the value of Big Data, there is no standardized approach for how to begin and complete a project. This how-to guide leverages our repeated success at working with enterprises to stand up Infochimps Cloud solution in complex organizations and technical environments.
We’ve narrowed it down to 4 key steps to successfully implementing your Big Data project. This part how-to, part working doc will empower your organization to achieve your defined business objectives through Big Data, regardless of the various technical environments.
This Template Also Includes:
- Real-life Use Cases
- Technical Requirements Worksheet
- Business Overview Worksheet
- Tips, Tricks, and How-To’s
Download Now and achieve a faster path to ROI; prove the value of Big Data internally; and scale to support more data sources and use cases.
“We’ve successfully empowered a number of Fortune 1000 companies with Big Data systems used to increase bottom lines, and we’ve done so at incredible speed. We’ve done this by combining the power of cloud as a delivery model, along with best practices represented in this project guide.”
Serial entrepreneur Jim Kaskade, CEO of Infochimps, the company that is bringing Big Data to the cloud, has been leading startups from their founding to acquisition for more than ten years of his 25 years in technology. Prior to Infochimps, Jim was an Entrepreneur-in-Residence at PARC, a Xerox company, where he established PARC’s Big Data program, and helped build its Private Cloud platform. Jim also served as the SVP, General Manager and Chief of Cloud at SIOS Technology, where he led global cloud strategy. Jim started his analytics and data-warehousing career working at Teradata for 10 years, where he initiated the company’s in-database analytics and data mining programs.