ENRICH A 360-DEGREE CUSTOMER VIEW WITH APACHE HADOOP AND SPLUNK

What began as a trickle is now the mainstream: Organizations are moving to the cloud for data management. No longer is the cloud just a cheaper place to park data; it is key to supporting business-critical innovation in advanced analytics, data science, and AI as well as for end-user business intelligence, data exploration, and data visualization. Data lakes and data warehouses running on market-leading platforms such as AWS are growing fast, just as they are on the platforms of competing providers. However, as cloud-based workloads grow in number and size, organizations are facing difficult data preparation challenges. The flow of data raw, diverse, and frequently unstructured can quickly turn cloud data lakes into impenetrable swamps. Without good data preparation technologies and practices, users of all types are frustrated; their productivity and satisfaction suffer because it’s too hard to get accurate data that’s appropriately transformed and structured for their purposes.

Digital transformation means that data drives more of our lives, more than ever. Data analytics is an essential skill for extracting information and meaning from data to support decision-making and power digital systems.

To preview your data, you must first have access to it. This operation can be difficult when distributed into different systems and silos which is why many companies choose to bring them together in a Data Lake. However, without governance or stewardship, these data lakes are rapidly turning into swamps, veritable brakes on innovation.

Denodo DataFest, the premier agile data management and analytics conference, returned once again to New York and London in 2018. Our annual user conference brings together industry analysts, subject matter experts, business leaders, data management leaders to discuss data strategies to enable a successful journey to the cloud, self-service BI, and data lakes with data virtualization. The event invited attendees to watch demos, hear customer success stories, and educate themselves on the best practice implementations of data virtualization.