Blog

March 4, 2019

In a recent article in Information Age we talked about how the worlds of big data and the cloud are preparing the path for the emerging concept of Data Lake 2.0. We believe that Amazon’s approach to the cloud-enabled data…

Google the word “CDO” today and your search will mostly results return articles about the “Chief Digital Officer”. However, if you came to this blog, you’re probably looking for guidance on the other title this acronym refers to: “The Chief…

Industry leaders know that their challenges with data analytics are spread across 4 areas: confirmation (‘the things they know they know’); intuition (‘the things they don’t know they know’); inspection (‘the things they know they don’t know’); and revelation (‘the…

Big data can translate to big wins for your company, but making it work means working smarter. Hadoop makes it simple to distribute storage and process very large data sets. Make Hadoop work for you even further by pairing it…

Congratulations! Your Hadoop cluster is up and running. Your data feeds work; your team knows how to manage the cluster, and expert users mine the data with Hive, Pig, Spark. But your executives aren’t satisfied. “Where is the business value?”…

Often times, customers approach me with questions around AtScale’s ability to integrate into the customer’s operational stack. Today, I want to highlight a component of AtScale’s Development Extensions called Webhooks. A webhook (also called a web callback or HTTP push…

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…

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…

February 12, 2019

Despite the existence of a plethora of data analytics tools, Microsoft Excel is still the preferred choice for many analysts working with data. With the continued growth of data, as well as migration to the cloud, accessing the data necessary…

The movement of analytical workloads to cloud data warehouses such as Google BigQuery, Snowflake, Amazon Redshift, and Microsoft Azure is a trend that will only continue to grow. The performance and cost benefits of these cloud providers compared to legacy…