…and how to fix them! We’ve asked our team of Talend experts to compile this top ten list of their biggest bugbears when it comes to jobs they see in the wild – and here it is!

Hello Talend Superheroes!!! Hope all of you are enjoying your time in Talend realm playing with different types of data. Many of you are old-timers of Talend, but everyday new developers are happily joining the band to learn about various superpowers related to data. Like any superhero movie, there is a learning curve to understand and manage the newly acquired capabilities the right way.

Sales and marketing analytics is one of the most high-profile focus areas for organizations today, and for good reason – it’s the place to look to boost revenues.

Today, enterprises need to collect and analyze more and more data to drive greater business insight and improve customer experiences. To process this data, technology stacks have evolved to include cloud data warehouses and data lakes, big data processing, serverless computing, containers, machine learning, and more.

Billions of times each day, application programming interfaces (APIs) facilitate the transfer of data between people and systems, serving as the fabric that connects businesses with customers, suppliers, and employees. Having the right API strategy in place can make the difference between success and failure when it comes to utilizing APIs to deliver results, reduce response times, and improving process efficiency.

Like any supply chain that aspires to be lean and frictionless, data chains need transparency and traceability. There is a need for automated data lineage to understand where data comes from, where does it go, how it is processed and who consumes it. There is also a need for whistle blowers for data quality or data protection and for impact analysis whenever change happens.

Well, let’s be specific here. Birds migrate either north or south. Data warehouses are only going in one direction. Up, to the cloud. It’s a common trend we’re seeing across every vertical and across every region. Companies are moving their existing data warehouses to cloud environments like Amazon Redshift. And more often than not –unlike their feather counterparts– ­once they migrate to the cloud, they never come back. But why? Simply put, it just makes sense.

Data professionals face an efficiency gap; they spend too much time to get access to the data they need and then put it into the appropriate business context. The capacity of delivering trusted data to business experts at the point of need is critical if you want to liberate data value within your company.

It’s no secret that the cloud data warehouse space is exploding. Driven by the need for on-demand, performant data warehousing solutions, businesses are turning to public cloud providers to modernize their analytics infrastructure and help them make better business decisions. Among the leading data warehouse options from the public cloud providers is Amazon Redshift. Redshift offers a petabyte-scale, fully managed data warehouse service in the cloud.