March 16, 2016 | Written by: Aislinn Wright
Categorized: Community | Data Analytics
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Traditional IT, supporting enterprise resource planning (ERP) systems with on-the-ground data warehouse and BI tools, has spent decades building a wall around a company’s data, lining it up in relational databases to make it readily available to run the nightly reports. At the same time, Web developers have been building customer engagement tools that produce large volumes of data in a semi-structured schema. This data is rich in customer insights, and so is the data the IT group has captured in transactional information.
For almost a decade, there has been a mounting cry that in order to create a full 360-degree view of the customer, these two data pools – structured and semi-structured – need to be combined.
RSG Media needed to draw from both “new” and “old” data sources in a way that was efficient, scalable and cost-effective.
RSG Media, a business solutions provider for the entertainment and media industry, realized that to stay ahead in the age of Netflix and binge-watching, it needed to draw from both “new” (cloud-based and non-relational) and “old” (on-premises and relational) types of data sources, and do it in a way that was efficient, scalable and cost-effective. It found that solution by moving its data warehouse into the cloud, with help from IBM Cloud Data Services.
RSG’s in-house data was stored primarily in Oracle databases, using SQL-based BI tools. Much of the new data available to the company is semi-structured, originating from social media, Web, mobile devices, and Internet of Things (IoT) sources, and stored in a range of NoSQL repositories.
Seeking a single solution that could efficiently integrate all this data and avoid technology and data silos, RSG found it was more effective to move traditional data to the cloud into the IBM dashDB data warehouse environment. IBM Cloudant served as an effective back-end data store for Web, mobile, and social data, and that data could be sorted and filtered into a relational database automatically using dashDB.
RSG Media’s Shiv Sehgal presents the Big Knowledge Project at TDWI Las Vegas 2016
RSG Media found that it was easy to put their existing talent pool to work in the new cloud environment. For example, the RSG Media data science team is experienced in the statistical language R, which runs in-database in dashDB via a convenient RStudio integration. The RSG team also uses Python along with R for data modeling, a combination which was easily implemented on IBM Cloudant.
From a change management viewpoint, the migration of RSG’s new data warehousing and BI environment to the cloud proved far easier and more efficient than had the company pursued a reverse strategy by building its own on-premises infrastructure to import and process new, non-relational data. All-in-all, RSG’s Big Knowledge project has proved to be a textbook example for why, when it comes to dealing with data that is “born on the cloud,” a cloud-first solution strategy is the only way to go.
To learn more about RSG Media and its data partnership with IBM Cloud Data Services, view the enterprise case study from Ovum, “Understanding Customer Viewership and Behavior Across Platforms: How RSG Media achieves a complete view of the customer with a scalable cloud database and analytics.”