Companies are being bombarded by new sources of data faster than they can consume them. The explosion of emerging customer data sources (social, clickstream, transactions, mobile, sensor, etc.) presents both a huge opportunity and a challenge.
The opportunity is that new data sources can reveal insights for applications that can drive competitive advantage. Businesses want to analyze and integrate more complex types of data to add new insights to what they already know about their customers to improve service and add more value to clients.
The challenge is that managing this growing volume and complexity of data is difficult with traditional database technology. As the volume of data grows, performance goes down. As data complexity increases, more administrators are required to organize data into something meaningful.
Apache Hadoop technology has emerged as a powerful and flexible big data platform for companies to store and process vast quantities of raw data over a long period of time. Companies no longer have to set limits on how much and what kind of data they can ingest into their data repositories. The mantra had become, “Keep it all in case it’s needed”. But to make the hordes of data useful, companies need a mechanism to transform the data into a valuable business asset. A new mantra is emerging, “Keep it all and let a data refinery sort it out.”
What is a data refinery?
A data refinery is a critical component of a big data strategy, especially for customer-facing enterprises that want to build robust and accurate customer profiles to improve customer interactions.
Think of it as an oil refinery where raw material (oil) comes in and is separated in the different streams for downstream production and products such as gasoline, motor oil, kerosene, and more. Similarly, a data refinery ingests raw material (data) into Hadoop in native format at any scale and can then refine it into other downstream systems or customer-facing applications. Raw data must be refined or explored to understand relationships and whether there is meaning in the data (through tools such as Apache Drill). Next, the data refinery cleans, enriches, and integrates data with other sources of structured data in downstream database or business intelligence solutions to deliver the insights that create more personalized customer relationships.
Harte Hanks builds a data refinery to improve data quality
To serve their clients better, Harte Hanks wanted to ingest and integrate more types of customer data into their clients’ contact databases. They wanted to gain new insights by getting access to the increasing volumes of data generated by people interacting with their clients’ brands over multiple channels. These insights could then feed into their clients’ marketing processes to help drive more effective marketing programs.
Harte Hanks knew their traditional database technology could not manage this huge increase in data volume and complexity, so they selected the MapR Distribution including Hadoop for its big data platform. A key component of the technology platform is the data refinery that cleanses and enriches the growing stream of new data sources that are ingested into the customer databases.
More data yields higher accuracy and new customer insights
The MapR data platform enables Harte Hanks to enhance the performance, scalability and flexibility of its solutions so its clients can more easily and quickly integrate, analyze and store massive quantities of data for deeper insights to better serve customers. This new solution enriches and enhances customer databases by integrating all kinds of digital data, survey data, reference points and more, all while maintaining the performance and ease-of-use they’ve come to expect.
Performance accelerates turnaround time to clients
Harte Hanks is able to increase customer satisfaction through faster time to value and more accurate data sets. Data processing that used to take one to three days can now be accomplished in hours, if not minutes. Their clients can put marketing insights into action immediately for faster results.
Better data = better marketing
The Hadoop-based data refinery can transform a deluge of data into invaluable company assets. Harte Hanks can now offer its clients faster and more accurate customer insights and more complete customer profiles so they can create smarter, more relevant and effective customer interactions.
About the author
Steve Wooledge, Vice President, Product Marketing, MapR
Steve brings over 12 years of experience in product marketing and business development to MapR. As Vice President of Product Marketing, he is in charge of increasing awareness and driving demand, as well as identifying new market opportunities for MapR. Steve was previously Vice President of Marketing for Teradata Unified Data Architecture. Steve also held various roles at Aster Data, Interwoven and Business Objects, Dow Chemical and Occidental Petroleum.
Steve holds an MBA from the Kellogg School of Management at Northwestern University, and a BS in Chemical Engineering from the University of Akron.