We did it again! The AtScale team was present at the Dataworks Summit 2018 in San Jose, California. We hope you had the opportunity to attend some, if not all, of the great sessions that we suggested. If you missed the event, don’t worry, we have prepared a great summary for you.
When we started AtScale five years ago, there were just five of us, driven by the desire to change the way enterprises deliver analytics to the business.
AtScale was born out of necessity. At Yahoo!, my team and I had grown frustrated that we couldn’t easily let users consume all Yahoo! data. Every day, my team had to work through the “anarchy of enterprise data”. Preparing data for business analytics required painful data movement and manipulation. And, no matter how much we optimized our data pipelines, keeping up with business needs felt like a losing battle.
Summer is fast approaching and big data is (still) growing. While you were preparing for the coming hot summer days, you may have missed some of May’s big data news. Without further ado, here is what you might have missed in May.
Organizations have come to the realization that data is a core part of their strategy and a scalable distributed computing platform central to their technology investment. However, a challenge that big data practitioners face is what use case they should first implement in their journey towards realizing their big data strategy. The reality is, multiple items need to be addressed: choosing the right technology, requisite funding, and the right technical talent. However, identifying the right use case with defined success outcome is the most crucial point of starting a big data project.
March is gone and Spring has arrived, at least for many of us. A lot happened in March, and we certainly don't want you to miss out on what’s big on big data. Without further ado, here is what you might have missed in March.
“Cloud computing” is that magnificent umbrella technology term that is broadly used to describe everything from ordering groceries online to keeping track of asset logistics across the globe.
If you are one of our avid followers, you might remember that, when we refer to “The Cloud”, we talk about the infrastructure that lets your people do data analytics at a wide scale. We’ve written pieces like “the 6 principles of modern data architecture” to provide a guide for how to ‘treat data’ through your modernization journey. And we’ve provided tools like the Data Maturity Survey to assess where you might be, along that journey.
This week, we’re sharing a piece from 451 Research that we think will help you survive through the inevitable ups and downs of your digital and cloud transformation.
Data Lake Intelligence with AtScale
In my recent Data Lake 2.0 article I described how the worlds of big data and cloud are coming together to reshape the concept of the data lake. The data lake is an important element of any modern data architecture, and the data lake footprint will continue to expand. However, the data lake investment is only one part of delivering a modern data architecture. At Yahoo!, in addition to building a Hadoop-based data lake, we also needed to solve the problem of connecting traditional business intelligence workloads to this Hadoop data. Although the term “Data Lake” didn’t exist back then, we were solving the problem of: “How can you deliver an interactive BI experience on top of a scale-out Data Lake” - it turns out we were pioneers in delivering Data Lake Intelligence.
Our experiences and learnings from those initial efforts led to the architecture that sits at the core of the AtScale Intelligence Platform. Because AtScale has been built from the ground up to deliver business-friendly insights from the vast amounts of information in data lakes, AtScale has experienced tremendous success and adoption in enterprises ranging from financial services, to retail to digital media. With the release of AtScale 6.5, we’ve continued to build on and expand AtScale’s ability to uniquely deliver on the promise of Data Lake Intelligence. If this sounds like something you might be interested in knowing more about… keep reading!
Poor February. The short month is dismissed for its brevity (let’s not talk about the weather) but a lot transpired the past 28 days, especially in big data and analytics. ICYMI, here’s a recap of the top stories:
It seems like only yesterday that we all gathered for the Strata New York Conference. And yet here we are, March is around the corner, and Strata San Jose is just a month away. Historically, Strata San Jose has roughly 5000 attendees while Strata New York averages closer to 7000 attendees. As one of the largest Hadoop conference in the US, Strata sessions focus on using data for competitive advantage. Strata Conference is also an opportunity to hear real life stories from enterprises who have been there, have the scars, and wrote the book. Strata is the ideal place to understand trends in the big data world. If you missed it, here are the [trends from 2017].
To learn from successful from Cloudera customers on how they succeed in BI on Big Data, check out this best practices webinar
The annual Gartner Data & Analytics Summit is just around the corner. As in past years, we are all anticipating the overwhelming sessions and agenda throughout this exciting week. This time in Grapevine, Texas (again)! In between sessions, catch a breath of fresh air and check out the exhibit hall to collect a bag of goodies to bring home. While T-shirts always make good pajamas, we may also wonder which sessions and vendors we should not miss. With all of the sessions available at the Summit, here are our suggestion on the ones you don’t want to miss!