Data analytics is key to the success of any industry — media, entertainment and sports included. Developing a single, unified view of any given product or person (whether a movie or show, actor or director, musician or tour, team or athlete) allows media, entertainment and sports companies to maximize revenue in a variety of ways. They would be able to, for example, compare performance of these entities against many variables, including region, genre, dates/windows, etc. They may also be able to leverage data to access rich intelligence about competitive products and gain deep insight into financial optimization, marketing strategy and consumer preference.
It is particularly difficult for companies within media, entertainment and sports to harness the abundance of data within and external to their organization:
+ Analysts are challenged to find the data they need: Products (e.g., TV shows) and people (e.g., actors) are constantly being viewed, reviewed, followed and rated by a multitude of external sources. This leads to extreme variety and volume of data across diverse sources, each organized and standardized in its own way, and companies often have a problem identifying which data assets are important.
+ Data source preparation is slow and not scalable: Even if organizations could find and access all of the relevant information, teams of data scientists and analysts are typically required to pull, combine and clean internal data (e.g. sales, marketing and financial) then integrate it with third-party sources for enrichment(e.g.social media data, ratings, reviews and other externally created datasets). Without standard identifiers or formatting to match entities between internal and external data sources, data preparation is arduous, unscalable, and error-prone.
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