As a vendor of dashboards, I know it’s really important how people use them to effectively communicate their data to end-users. But I believe a well-designed dashboard is a rare thing.

In the past few years, we’ve seen rapid adoption of a new data analytics stack, based on cloud warehouses like Amazon Redshift, Google BigQuery and Snowflake. This stack has three layers: Data Integration, Modeling Layer and Application Layer.

The term API – Application Programming Interface – refers to the set of communication protocols or rules which allow an application to access the features of, or data contained in, another operating system or program. APIs can make it possible for companies to build rich and accurate profiles of their customers by aggregating data about them from multiple computer systems, inside and outside the enterprise.

Suppose you have data in Google Sheets that you want to bring into your data warehouse to join up to other data for better BI. You could use Talend Cloud Integration, but you don't need to do complex transformations and you don't want to spend a lot of time. What about Stitch Data Loader? Stitch is a great ELT platform, able to move millions of rows from more than 100 data sources with just a few mouse clicks, but it doesn't provide a native integration for Google Sheets.

Investment in artificial intelligence (AI) is growing, with 60% of adopters raising their budgets 50% year over year, according to Constellation Research. But working with AI under emerging privacy standards is complex, requiring a dynamic balance that allows for continued innovation without misstepping on regulatory requirements.