Keeping resolutions is hard. Research shows that most of us fail to follow through on our new years' resolutions by the second week of February! We are hopeful that 2018 will be different though! In this contributed piece, Donald Farmer takes us through his best practices for marking and keeping resolutions. Donald is highly respective figure in the Data Analytics world and has built outstanding product franchises at Qliktech and Microsoft. He is currently Principal at TreeHive Strategy, an I.T. advisory firm.
Throughout the year, our team engages in lots of meaningful conversations with the Big Data community, customers, partners, analysts and press. We cherish these moments because they are a great source of information and learning. Below some of the moments that made our top 10. The list includes press articles, videos, research links and other resources that we believe were particularly meaningful in 2017.
It’s becoming more and more crucial for businesses to find ways to gather, use, and analyze big data. After all, big data is by far the most effective tool for keeping accurate and thorough track of customers and employees, as well as the most efficient way to predict future behaviors. However, big data is notoriously complex, unstructured, and massive, making it extremely difficult to manage without the proper tools.
We Told You It Would Be Cloudy
You have probably already heard all about it, read all about it and know all about it, but if you are anything like me, (or Einstein) you have already figured out that the more we learn about BI on Big Data the more we realize how little we know. Or, do we?
The Forecast Calls for Cloudy Weather
You don’t have to be a clairvoyant to know that there is an ever-increasing trend in cloud adoption among start-ups and enterprises alike. In the world of Big Data, the past few years have shown a significant increase in cloud adoption. While Amazon initially led the way with cloud data products - with Amazon Elastic MapReduce (EMR) for Hadoop and Redshift for data warehousing - the past 12 months have seen new entrants on the scene.
Is it October already?
It’s hard to believe that October is here. It feels like only a few days ago that we released AtScale 5.0 and AtScale 5.5. Both releases contained a number of great new features that I was excited to share with the Big Data and Business Intelligence communities. Although I may be a little biased, I really do believe that the release of AtScale 6.0 marks one of the biggest releases in the history of the company.
The AtScale team is looking forward to the 2017 Tableau Conference event in Las Vegas. Never did we imagine that we would be attending under these circumstances. We would like to take a moment to express our sympathies to those affected by the tragic events that took place earlier this week. If you would like to support the victims of these events, please visit this link for more information on how you can help.
It’s that time of year again. Join AtScale in Las Vegas at the Tableau Conference Oct 9-12 where we will be showing you and the other 12,000 BI experts how AtScale can help you seamlessly use Tableau with your favorite Big Data platform.
Almost 5 years ago to the day, my co-founders and I opened the door of our company in downtown San Mateo. It was just the five of us, driven by the desire to make Big Data work. We had been scarred by complex Big Data analytics projects in our former lives and were frustrated that the Business Intelligence market didn’t have a good solution for the data stored in data lakes.
Since then, the AtScale team has grown to almost 100 talented folks. Our company has not only received the trust of great investors (we announced our Series C today), we have also grown into a technology leader that has driven success at many enterprises.
AtScale does it again! Will you be one of the 6,000 Big Data experts joining us this year? Once again, our team is headed to the Javits Convention center in New York for the 2017 Strata Data Conference. Come see us so we can have great BI on Big Data discussions during this magnificent event.
Despite the challenges associated with data warehousing, enterprise IT leaders have accepted it as a necessary evil of deriving value from information within Hadoop and other Big Data ecosystems. How much does it cost to create data warehouses or datamarts that extract data out of Hadoop? Is there a better way to do BI on Big Data?!