AtScale Blog

 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?

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.

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?

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 API) is a way for an application to provide other applications with real-time information. A webhook delivers data to other applications as certain events occur, meaning you get data immediately as opposed to a REST API which you would need to poll for data very frequently in order to get it close to real-time. This makes webhooks much more efficient for both provider and consumer.

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.

If you are like me, a Tableau fan, you’ve probably used Tableau for many years, attended numerous Tableau Conferences, and cheered with great enthusiasm when the engineers at Tableau demonstrated the latest and greatest enhancements to the software.  You may also be very accustomed to creating your own calculations based on the row level data you are connected to.  You enjoy the freedoms that Tableau offers.   

“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.

How valuable is an insight if you don’t know what’s driving it?

The investment in big data made in recent years by companies has been significant. Many are now looking to capitalize on the insights to be discovered in their expansive data lakes. Developing an analytic solution is a difficult and laborious process. More than a few projects have been abandoned long before any conclusive benefit is realized. Some efforts end due to constraints on time and money, others as a result of bad design or poor end user adoption. That last point is significant. You’re going to spend considerable resources to empower your decision makers. If you build it, and they don’t come, then what?

Congratulations!  Your data is controlled, aggregated and turbocharged in your AtScale virtual cube.  You have Tableau to create remarkable visualizations. Your data is happy! But are your cube designers and business users too? For instance, did you know that centralizing calculations in your AtScale Virtual Cube eliminates TDE perpetuation, 3rd party ETL processes and version control headaches?  For an enhanced AtScale experience, here are 5 Best Practices you should be implementing in order to maximize AtScale on Tableau.