The joy of working as a Customer Success Solution Architect is that I have the opportunity to work with many different customers and each challenges us with a different Big Data use case.
I've worked with enterprises that offload their Netezza database into the cloud. I've seen companies analyze social media data in real-time. I've helped teams streamline operational processes and increase efficiency in production lines. Big Data provides enterprises a competitive advantage and reduces operational costs across a these varied scenarios. However, setting up a big data environment is not for the faint-hearted - or is it?
As the World Cup is kicking off, some of us might be spending a lot of sleepless nights (or waking up earlier) to watch the games. Here is a fun fact: the most anticipated match is from Group H, Japan Vs Belgium (with 4.9B page views out of 9B page views). Interesting.
We definitely want to make sure you don’t miss out on your big data news while you’re enjoying soccer games, here is what you might have missed in June.
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.
If you're a sucker for great market data like I am, you must have heard of Mary Meeker. Mary is partner at Kleiner Perkins Caufield & Byers. She's known in the Valley as a specialist in digital businesses and has been credited with having a deep understanding of what makes businesses succeed and fail. Earlier today, she released the 2018 version of her internet trend reports: 294 slides delivered in 30 minutes on the Code Conference stage. You might not have caught everything. Here are our highlights.
2018 Dataworks Summit is just around the corner. As you’re preparing your travel to San Jose, it’s time to think about how to maximize your time at the Dataworks Summit. Dataworks Summit will take place from June 18 to June 21. Sessions, keynotes, and workshop are spread across eight different tracks. Check out the full agenda. Everyone may have different goals for this summit. While you’re going through the agenda to select the best sessions for you and your organization, here are our recommendations.
“We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run” - Roy Charles Amara
Mr Amara, an American researcher and futurist, probably didn’t anticipate how much wisdom was encapsulated in just a few words. Buying technology is hard. And Enterprise IT buyers are often left with the hard task of determining if the new piece of technology they just heard about is pure hype or if it has hope. Where are they to find consistent guidance?
It may seem like only yesterday that we said goodbye to 2017, but we are almost half-way through 2018. Big things in Big Data happened in the month of April. Many of us watched Mark Zuckerberg testify in front of Congress about data use and security, and still await the final outcome of Cambridge Analytica’s data abuse. If April seemed like it slipped under your fingers, check out what you might have missed in the world of big data.
My previous blog highlighted some best practices to gain immediate value from all the capabilities that AtScale offers when using Tableau as your BI tool of choice. One of those best practices is to use AtScale-created date dimensions to improve query performance, which is particularly helpful when using date dimensions as filters.
Five years ago we had a hypothesis that Business Intelligence (BI) needed a reboot. We planned to take the best parts of original BI ideas and merge them with modern engineering and data analytics to build a platform for delivering self-serve, secure, curated and fast analysis to the entire business. Our strategy, we believed, would build a bridge from the old world to the new world while giving us a stage to present new concepts that made Business Intelligence truly intelligent.
The joy of working as a Customer Success Solution Architect is that I have the opportunity to work with many different customers and each challenges us with a different Big Data use case.
