Intel’s Integrated Analytics Platform Helps Sales and Marketing

October 26th, 2015 |
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IT Best Practices: Intel IT is building an analytics platform that integrates and connects business intelligence (BI) data using a data lake model to reduce insight latency from months to days. Eventually, we aim to reduce data insight latency to 24 hours.

A data lake is a repository for large quantities of structured and unstructured data. It allows for more versatility than a data warehouse because we can ingest data from various streams at various rates and according to various data models and file formats.

Intel’s sales and marketing organizations rely on BI solutions from Intel IT to help make smarter data-driven business decisions. Analytics solutions in environments that are incapable of interconnecting datasets weaken the business value we can provide sales and marketing.

The Integrated Analytics Hub (IAH) delivers the following benefits to sales and marketing:
•By implementing a data lake model using Cloudera’s distribution of Hadoop* (CDH), we provide data scientists, analysts, data stewards, and end users faster and more flexible access to large volumes of data. The data is available in multiple formats and in three states—raw, cleansed, and conformed—for various levels of analysis.
•All users can more easily engage in self-service BI and use BI front-end tools of choice for analysis of data at any of the three states.

•The ability to interconnect datasets and share visualizations, reports, and dashboards on the self-service BI portal increases velocity and removes manual IT intervention.

Data analytics projects have already accounted for an estimated quarterly savings on marketing digital-media expenditures of approximately USD 170,000. We continue to optimize IAH to increase automation and develop applications that can simplify and accelerate self-service BI.


For more information on Intel IT Best Practices, please visit intel.com/IT
 

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Posted in: Big Data, Information Technology, Intel, Intel IT, IT White Papers, IT@Intel