Xplenty provides features to efficiently extract, transform, and store data from various sources. Chartio provides Visual SQL features that let us explore and analyze data. Furthermore, it includes functionality to arrange charts and metrics in dashboards that can be shared. Both these tools can be used synergically. In this post, we will cover how you to configured Xplenty to use Chartio data. In a subsequent post, we will explain how to visualize the data provided by Xplenty in Chartio.

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.

Are you asking yourself the question “what is no-code”? You’re not alone. The concept sounds almost too good to be true: developing your own software applications without ever having to learn a programming language like Java or Python. Even your most technophobic employee can become a star software developer thanks to the proliferation of no-code development tools.

How vulnerable is your sensitive data? Your data policies may put this information at risk of being breached. An ad hoc approach for dealing with this data makes it difficult to maintain your organization’s cybersecurity. Data obfuscation holds the key to improving your security and making it easier to use your data, but it must be driven by your policies to be effective.

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.

Organizations are swimming in data, but are they actually getting the most value out of it? A recent report by Seagate and IDC found that while enterprise data is projected to increase at 42.2 percent annually over the next two years, up to 68 percent of it may go unused.

When cyberattacks take out business systems, organizations suffer from direct and indirect financial losses. When healthcare systems go down, it’s a matter of life and death. Healthcare organizations were already a frequent target of cybercriminals, and the pandemic has made this situation worse. Infosecurity Magazine reports that healthcare data breaches will increase by 3x in 2021, at a time when so many healthcare providers are burnt out and exhausted from battling the pandemic.

Introducing Apache Hadoop to an organization can be difficult. Your workforce is trained and experienced in SQL and the analytics tools that integrate with it. However, when you reach a point where the data is too big for a MySQL server, stepping up into the world of Big Data becomes necessary.

Modern applications don’t function in isolation. To get the most out of the enterprise apps you build or buy, you’ll have to connect them to other applications. In other words, data engineers have to engage in effective application integration to achieve their business goals. Sometimes, this means connecting one application directly to another. But this is a rare occurrence in digitally transformed industries.

From system logs to web scraping, there are many good reasons why you might have extremely large numbers of small data files at hand. But how can you efficiently process and analyze these files to uncover the hidden insights that they contain? You might think that you could process these small data files using a solution like Apache Hadoop, which has been specifically designed for handling large datasets.