eCommerce analytics involves tracking a wide range of metrics relating to the complete journey of the customer, right from discovery to acquisition, conversion, retention and advocacy. Analytics lays a foundation framework for any eCommerce business and it helps them understand which marketing and sales initiatives are working, those that aren't, and the areas that have a great potential for growth.

The healthcare industry has always been flooded with a huge amount of complex data, coming in at a very rapid pace. The industry also faces constant challenges such as the growing demand for services, rising costs and a workforce that is struggling to meet the needs of its patients.

The 'data lakehouse' is quickly becoming popular in the data analytics community. Data lakehouse architecture combines the benefits of a data warehouse and a data lake. It aims to merge the data warehouse’s data structure and management features along with the flexibility and relatively low cost of the data lake. Watch this panel discussion to learn how the data lakehouse can address the limitations of the data lake and data warehouse architecture to deliver significant value for organizations. Explore why the data lakehouse is an ideal option for enterprise data storage initiatives.

Building a data warehouse is an expensive affair and it often takes months to build one from scratch. There is also a constant struggle to keep up with the large volumes of data that is constantly generated. On top of that, setting up a strong architectural foundation, working on repetitive and mundane data validation tasks and ensuring data accuracy is another challenge. This puts tremendous stress on data teams and data warehouses. Data warehouse automation is intended to handle this growing complexity.