Enhance your Customer 360 architecture with Gluent Data Platform

At Gluent, we work closely with several modern data platform / data lake / cloud vendors and I always try to find some time to learn a bit more about them throughout the week. Recently, I came across a slide deck about Cloudera’s position on using Big Data for your Customer 360 initiative. The presentation, “Using Big Data to Drive a True Customer 360" (embedded below), describes several use cases and offers up Cloudera’s approach to enabling a true Customer 360 experience with the use of their Enterprise Data Hub (EDH).

Using Big Data to Drive a True Customer 360

So what exactly is Customer 360? Beyond being a common buzzword in the data integration and analytics industry, it’s quite an important process for many companies. The slides do a great job of explaining it, but of course they are in PowerPoint format with no commentary. The main focus is how an organization can use all available data about their customer to gain a full, 360º understanding of who she is, how she interacts with their products / services, what she has purchased, how she browses around their website, and many other interactions that help to define what the company must to do to improve her experience and ensure she remains a happy customer. Delivering a consistent message, personalizing customer experience, marketing campaigns, and various other processes are driven by Customer 360 initiatives.

Image from “Using Big Data to Drive a True Customer 360”, slide 5

Back to the presentation. Once I saw Data Silos listed under the “Key Challenges in Driving a Customer 360” slide I started thinking about how the Gluent Data Platform is essentially built to enhance the architecture. And just below that, New Data Sources, which also include semi/un-structured data, is also a great fit for Gluent. The enhanced architecture could help answer these questions: How are these silos moving data to the Enterprise Data Hub? What if some of the siloed applications could benefit from additional data sources or, better yet, the enriched data from the EDH? Gluent can help in these scenarios, complimenting the Cloudera components and overall simplifying the data integration.

Further into the slide deck is Cloudera’s “Customer 360 — Flow with EDH” diagram. I created a very similar, yet slightly modified, version of the architecture to show exactly how the Gluent Data Platform might enhance the Customer 360 data flow.

Gluent Data Platform compliments the Cloudera Enterprise Data Hub nicely

The core Enterprise Data Hub remains at the center of the Customer 360 story, but how data is moved physically or accessed virtually changes a bit. Let’s walk through the numbered items in the image to find out how.

  1. Gluent Data Platform has the ability to bring the siloed “structured” data sources into the EDH using the Gluent Offload component. Rather than build your own Sqoop process, or maintain multiple native application data extract components, Gluent provides the offload of data with the run of a single command. All of the details, such as development of the data movement process, creation of the Impala tables in Parquet format, and any partitioning, optimizations, and data validations required, are all completed for you within this single command. 
    Gluent can also provide the various customer-focused source applications with access to any data stored in Hadoop, including the enriched data that is transformed within the EDH. Gluent Present enables the applications to access virtual tables in the RDBMS using transparent data virtualization, leaving the storage and query processing to be completed using the power of the Enterprise Data Hub.
  2. The Enterprise Data Warehouse (EDW) currently provides Business Intelligence (BI) tools with the aggregated data necessary for the marketing analysts, customer support folks, or other consumers of the information to make informed decisions on a daily basis. With Gluent Present, the Customer 360 data that is captured and processed through the EDH can be virtually shared with the EDW to enhance these reporting datasets. Gluent can also sync data from the EDW → EDH for further enrichment or sharing across various channels.
  3. Most Business Intelligence tools now have the ability to connect to and access data stored in Hadoop / Kudu / etc. But, not all reporting functionality might work against the datasets when using Impala SQL. For example, if the organization has standardized across various Oracle PL/SQL based functions for certain business rules, these would have to be rewritten to work in Impala, maintained multiple places, etc. Rather than spend effort and budget there, simply present the EDH data to the EDW and continue pointing the BI tools directly the EDW (which likely have loads of these procedures and functions built up over the years).

With the rise of the Chief Data Officer (CDO) role, his/her various responsibilities to an organization include managing data as an asset. One aspect of data management is the consolidation of data, transforming it into useful, relevant, and timely information. With that, a large part of the CDO’s role is to enable the Customer 360º view to drive decisions throughout the company. Gluent’s vision is to provide all applications access to all enterprise data, at anytime, without any code rewrites or migrations. That fits nicely with the CDO’s fundamental mission of data consolidation. Reach out to the Gluent team at info@gluent.com to find out how we can help simplify your Customer 360 implementation.