Sentiment analysis offers powerful business intelligence to enhance the customer experience, revitalize a brand, and gain competitive advantage. The key to successful sentiment analysis lies in the ability to mine multi-structured data pulled from a variety of sources into a single database. Learn how a big data platform can help you get more value out of sentiment
A 360-degree customer view offers a deeper understanding of customer behavior and motivations. Obtaining a 360-degree customer review requires analysis of data from sources like social media, data collecting sensors, and mobile devices. From there, more effective micro-segmentation and real-time marketing often result. Learn why big data analytics offers a more complete picture of the consumer.
Ad-hoc analysis only looks at the data requested or needed, providing another layer of analysis for data sets that are becoming larger and more varied. Big data ad-hoc analytics can help in the effort to gain greater insight into customers by analyzing the relevant data from unstructured sources, both external and internal. Learn how about a how big data cloud service makes ad-hoc analysis easier in Hadoop.
Systems that offer real-time analytics quickly decipher and analyze data sets, providing results even as data is being generated and collected. This high-velocity method of analytics can lead to instant reaction and changes, allowing for better sentiment analysis, split testing, and improved targeted marketing. Learn more about how your business can benefit from real-time analytics.
Multi-channel marketing creates a seamless experiences across different types of media like company websites, social media, and physical stores. Successful multi-channel marketing requires an integrated big data approach during all stages of the buying process. Learn more about how a big data platform can streamline your multi-channel marketing.
Customer micro-segmentation provides more tailored and targeted messaging for smaller groups. This personalized approach requires analysis of large sets of data collected through customers’ online interactions, social media, and other sources. Learn more about how companies are using big data to better segment and target customers.
Ad fraud detection requires data analysis of current fraud strategies by recognizing patterns and behaviors. Data that shows abnormalities of group behavior make it so ad fraud is detected early and stopped before it is spread. Learn why businesses are turning to big data platforms to combat ad fraud.
Clickstream analysis helps to improve the user experience by analyzing customer behavior, optimizing company websites, and offering better insight into customer segments. With big data, click stream analysis helps to personalize the buying experience, getting an improved return on customer visits. Learn more about the impact of big data on clickstream analysis.
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.”