Have you changed the way you use big data in your business? Understanding the rapid pace of data usage across your organization and planning for the future of big data is a key skill.

Learn why Enterprise clients use Pepperdata products and Services: https://www.pepperdata.com/

#FutreOfBigData #BigDataPerfromance #Pepperdata

Sometimes we all need a little insight.

During this webinar, hear from industry leaders, Ahmed Kamran Imadi, Big Data Solutions Engineering at Fortune 100 Financial Institution, Mark Kidwell, Chief Data Architect at Autodesk, Satish Nekkalapudi, Sr. Manager at Magnite, and VP of Customer Success Joel Stewart at Pepperdata about what role big data is playing in their business today and how they are adapting their IT ops and development teams to keep pace with change.

Topics include:

• What will be big data’s role in the future for business and how will IT adapt and grow?
• How will the growth in big data affect IT ops and developer processes today?
• Will this change skill sets for these roles?
• What skills will be needed in IT as the need for big data increases?

More on the episode:
To start with, how has digital transformation affected the role of big data in your organization? So, for the intro and the question, I'm glad I had a few minutes to prepare some responses just to these for this one, you know, in particular, where I'm at now the digital transformation was well underway, but here at Autodesk and some of the companies I've been at before, one of the key things digital transformation meant for analytics or data processing teams was that the products were always online, always available to the company's customers and users.

And with that came this flood of data usage, data or behavioral data, whatever it was that wasn't previously available. And of course, with the data comes this huge demand to process that data to derive insights, from insights from it, so the, you know, the main driver is probably the last several companies I've been at that have undergone this, has just been unlocking the behavioral insights, and being able to use those to drive marketing, or recommendations, or other common analytics use cases.

For companies that are really advanced, they're using it to drive analytics of product behavior or performance, crash reporting, other insights, and basically predicting things that customers didn't know about their products. Or, the way they're using the products and being able to offer those back as insights so that those things sound great. When somebody starts a digital transformation, doing all that work and delivering that is the real effort for us.

Satish, same question for you. How has the digital transformation affected the role of big data in your organization? Satish, we can't hear you at the moment. I don't know if you have a, oh can you hear me now? We can. Thank you. Yes, sorry about that. Yep. Now, Magnite has a lot of data coming in through our ad engines, and bit engines and stuff. We have been collecting the data and with, during the digital transformations, and all of this processing, our data science team has come up with a lot of algorithms that help both our publishers and then the buyers, and the demand partners as the stuff we also enabled.

A lot of optimizations in our platform in such a way that our ad engine clusters and bit engine clusters were equally sized, which didn't help Magnite in a lot of ways. So, during the transformation process, we reduced we based on the algorithms suggested and stuff. We were able to reduce the bidding, understand the bidding patterns, and reduce our billionaire clusters which enabled our power up our ad engine clusters which enable the whole amount of data that passes through our RTB platform.

This is why we jump from tens of billions of requests to hundreds of billions of requests with a minimal set of changes, which is completely powered by our data science team. And then, big data also powers our reporting and analytics, which is one of the first cutting-edge platforms in our field. And this helps us slice and dice data for our customers at the second level, whereas it takes from other partners which for ours together and improved transparency in the whole processes by providing log-level data access, and also enabled our brand production team to identify any malicious actors and cut them off as early as possible....

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