The data lakes concept has come back into popular focus with Amazon Athena, an innovative, serverless solution. But does it fit into your organization’s data stack? This article covers Amazon Athena capabilities, pros and cons, competitors, and use cases.
Businesses today have a growing demand for real-time data integration, analysis, and action. More often than not, the valuable data driving these actions—transactional and operational data—is stored either on-prem or in public clouds in traditional relational databases that aren’t suitable for continuous analytics.
With the expectation to become a $623 billion market by 2023, cloud computing is firmly planted in the technological field. Specifically, the more information that’s created, the higher the demand there is for quick access and manipulation of that data. Therefore, what cloud services offer to end-users is usable and essential: unlimited data storage, disaster recovery, and worldwide access.
As a result of overwhelming excitement (and pressure) from my fellow Qlikkies, I’m going to share with you the recent demo I did at our all-company annual kick-off which shows Active Intelligence in action. It was intended to be an “internal-only” demo because it mixes existing capabilities with near-term future ones, but, on reflection, I think you, too, will be just as excited.
If you're a developer trying to ETL data into and out of Heroku, the seemingly shortlist of options may disappoint you. Heroku itself promotes Heroku Connect, but this expensive solution might not even integrate with all the systems you use (like AdWords and Facebook), making it difficult to get a holistic view of your data. Fortunately, Heroku Connect isn't the only solution. In fact, there are several third-party ETL tools that can help you get your data in and out of Heroku with ease.
