Video: The State of Data in Video
Learn more about data and analytics at Streaming Media's next event.
Watch the complete panel from OTT Leadership Summit, OTT103. The State of Data in Video--Toward an Automated Future, in the Streaming Media Conference Video Portal.
Read the complete transcript of this clip:
Diane Strutner: Across the board, any industry you go to, everybody is struggling with data. And they're specifically struggling with creating clean, relevant, and labeled data sets to be able to use for newer technologies like AI and machine learning, and to have a better understanding of their business, and where they need to go in the next few years.
The video space is no different. Today's industry, we all suffer from not having standardized, centralized, and organized data sets. It's very difficult today to make decisions with the data we have. It's stuck in silos, there's subjectivity added into it, it's not in real time, and all this leads to not being able to make the strategic improvements that video publishers and all of the vendors and infrastructure providers that support them need to make the business of video better.
So, what data do we have today, and how good is it? Let's first define what good data is. Data quality is measured by both accuracy and precision. So, we can see here a few examples of we have completely inaccurate and precise data, we have precise data but it's inaccurate, imprecise but it is accurate, and then holy grail of having both precise and accurate data.
How do we actually define accuracy and precision? So, today these are really defined by what calculations that we're using today, and how we're actually measuring the data in the first place. Singular data points and measurements actually don't tell the whole story for us. So, a lot of us here come from different parts of the video streaming space. We might come from video playback, video delivery, video preparation, even the creation of content.
We are actually all part of this end value chain. So, by looking at information just from one part of this end-to-end process, we're not going to better understand the impact across all of these systems. To understand data points really means understanding data in context, which means bringing together data from across all of these different parts of the playback, delivery, preparation, and creation of content today.
So, what we really want to talk about is, the future of data really looks like an end-to-end datatecture, where we have data that's coming from video playback. It's pulled in from the process of delivering this video, the creation of all of this content, and it involves making core changes to how we're aggregating data, transforming, standardizing, joining, routing data to share with other industries. And we should be using data, at least, to send feedback loops of information and reports to a lot of different types of tools today. So, data warehouses, our delivery partners, our advertising partners, our content creation partners.
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