The need for Big Data in the Entertainment Industry has reached critical mass: as data grows exponentially on the Internet, on mobile devices and on social media platforms, studios and media companies have an unparalleled opportunity to mine data for insights about what consumers want. The benefits from Big Data solutions ability to provide real-time, accurate information on what customers are listening to, downloading and buying can help target marketing activities and inform new product launches for Media companies and Studios.
Unfortunately, due to the sheer data volumes involved, conventional database technologies struggle to work well with real-time data. Scalable Big Data software such as Hadoop has a high barrier to entry since it requires advanced skill sets to implement as well as requiring development time to create and modify individual queries. For studios that rely on day-to-day decision making through data, this makes it very difficult and expensive to implement, use and learn.
When it comes to the music industry, Big Data is often about using a Variety of multiple data sources. Studios have a variety of data sources to choose from when it comes to Big Data analysis. Digital sales logs from vendors such as Amazon, iTunes and Spotify can show what customers are buying in real-time. E-commerce vendors such as Magento can provide sales logs. Point of Sale data from retailers such as Best Buy, Target, and Walmart can provide tremendous datasets. Aggregators such as Anderson and Nielsen SoundScan can be used to get views across multiple vendors as well.
Combine sales data with with leaderboards from Nielsen, NextBigSound, MediaBase and others to see what’s hot. You can even use social media data, such as Tweet activity, upvotes on various consumer-facing media sites and Facebook data.
Pulling all of these data sources into one dataset is extremely helpful. But once you pull together all of these real-time streams, you find that you need a high-performance analytic platform that can work with it.
Enter InfiniDB. InfiniDB loads in massive amounts of data, quickly and cost-effectively, and allows any MySQL developer to query it and receive results in seconds for even the most complex queries.
Use InfiniDB for:
- Granular analytics – look for patters on who brought what, where, when and for how much. Look at purchase attribution, customer web analytics and market movements. Identify cross-sell and up-sell opportunities, rising stars, popular trends and more!
- Time series analysis – look at purchasing trends over all of your data. No need to sample the dataset or only look at the last several months.
- Effortless scalability – due to InfiniDB’s scale-out, Massively Parallel Processing technology, adding data from additional sources is not an issue. You can provision nodes as needed and increase your processing power without involving IT.
Best of all, due to its native MySQL interface, InfiniDB works well with reporting platforms such as Tableau, Pentaho and MicroStrategy. InfiniDB can read and write to the Hadoop Distributed File System (HDFS) through an open-source Hadoop Connector. Coming in 2014, InfiniDB will be able to directly work with files in HDFS as well. Due to its versatility, InfiniDB is often used as the analytic engine alongside a variety of general-purpose databases such as Oracle, Teradata, MongoDB and Cassandra.
The strength of Big Data comes from using multiple data sources for ad-hoc analysis. InfiniDB gives you a powerful, easy-to-use, cost effective platform for Big Data analytics across your whole team.
See more information about how Warner Music Group, an InfiniDB customer, uses InfiniDB for ad-hoc analysis.