As Qubole Data Service is a source of strategic advantage, this client has asked that its name not be used.
An award-winning, full-service digital advertising agency based in the United States. The digital advertiser leverages Big Data to help its more than 3,000 clients make smarter decisions.
Evolving digital advertising dictates increasing levels of personalization designed to scale to millions of users. To remain competitive, it needed to deploy advanced contextual and behavioral targeting and micro-segmentation to help its clients boost the return on investment of their online efforts.
Architectural Overview: The advertiser was relying on a traditional data warehouse to deliver insights based on historical consumer data such as purchase history, campaign responses and customer profiles. However, the growth in the importance of online behavioral data such as user clicks, page visits, contextual activity and social and mobile data led to Big Data requirements that were well beyond the capabilities of its data warehouse.
Deeper personalization required integration of data from a complex digital advertising ecosystem, including AppNexus for advertising management, Google Analytics, third-party data suppliers such as Axciom and Experian, offline CRM systems such as salesforce.com, social media profile data, and mobile data streams.
Although the digital advertiser recognized that the Hadoop platform would provide the ability to meet the high-volume, velocity and variety of Big Data required for digital advertising, it found that Hadoop was difficult to use and had trouble getting started. In particular, the company could not build a data pipeline, the steps going from data acquisition to transforming data into Hadoop to production deployment of algorithms, in a repeatable and consistent way.
The digital advertiser estimated that its internal implementations of Hadoop would require millions of dollars in upfront investment. Failure placed not only this investment at risk, but the advertiser was concerned that being unable to deliver on business objectives in a timely manner would be even costlier.
QDS tackled the digital advertiser’s tough structured and unstructured data integration challenges using its pre-built connectors for on-premise, cloud and social media data sources. No changes to the digital advertiser’s on-premise infrastructure were required.
Qubole provided a managed Big Data service that made it simple for the digital advertiser to prepare, integrate and explore Big Data in the cloud. Using QDS, the advertising could turn its attention to its business requirements rather than having to deal with the complexities of Hadoop, managing clusters or scaling its infrastructure. The QDS Amazon S3 loader and Sqoop-as-a-Service delivered an automated and reusable data pipeline.
Not only did the digital advertiser deliver its project in record breaking time, it saved a few million dollars of upfront investment by going with QDS. The company found that its monthly could bills were half the price of other options.
With QDS, the digital advertiser has been able to use Big Data insights derived from QDS to:
“We realized that we had to implement Hadoop quickly to keep up with digital advertising trends, but found the platform overwhelming. Qubole Data Service helped us get up and running quickly so that we could deliver the micro-segmentation, contextual and behavioral targeting and optimized campaign performance our clients were demanding.”
Qubole is a significantly more polished product than EMR. Data scientists can explore their data in S3, create tables and query those tables all via an easy-to-use web UI
Qubole’s fantastic support has been key in our successful deployment. They continue to deliver of new features and revisit the ones that we ask for
Our goal at MediaMath was to take our existing industry leading infrastructure to the next level handling new complex analytics tasks. Qubole has helped us enable this goal with minimal risk.
Instead of worrying about provisioning clusters of machines or job flows or whatever, Qubole lets you focus on your data and your queries … The Qubole guys have been extremely helpful!
The service spins up users’ clusters only when a job is started, then automatically scales or contracts them based on the workload, and spins the servers down once the job is done.
Qubole’s Hadoop and Hive interfaces are vastly superior to the default CLIs, which scare business analysts and hinder meaningful analyses of the gaming logs that we collect. With Qubole, business analysts are self-sufficient in using a Big Data platform to meet their advanced analytic needs.
Online Gaming Company
top-performing technologies in the data industry are definitely taking aim at democratizing data tools and bringing the power of data to smaller businesses. This is a major change in the data industry, and Qubole Data Service is a great example
I’m very happy to be using Qubole in production. Qubole has saved me a lot of time, effort, and trouble in getting my data processing pipelines up and running. My data pipelines process Appnexus data in Amazon S3 which is then stored in Vertica. The engineering team understands the complexities and provided awesome support!
Real-time Ads Retargeting Startup
There’s a whole world of web companies, SMBs and other non-Facebooks or Yahoos that will want to use Hadoop but not want to run it in-house…offering a cloud service makes it easier for these users to get started with the platform and for Qubole to keep improving.
Qubole offers a big data ETL and exploration service through auto-scaling Hadoop clusters with a web user interface for data exploration and integration with various data sources. The service can do (nearly) everything EMR can do, and it goes further
Big Data Republic
Simba knows Big Data access. Qubole knows Big Data. Qubole’s founders authored Apache Hive, built key parts of the Hadoop eco-system and brought Apache HBase to Facebook
“The integration of Tableau and Qubole makes it faster and easier for our customers to operationalize Big Data…lowers the resource barriers to deriving the benefits of Big Data because customers can deploy our joint solution seamlessly and cost effectively.”