COVID-19 introduced an unprecedented level of volatility in world markets, and the shockwaves that arrived in its wake exposed a wide chasm between two main types of multinational organizations: Those with agile internal processes and those without. In a world built on complex and globalized supply chains, COVID-19 tested that internal agility, sometimes to breaking point.

Never before has data become so prevalent in everything we do. Sorting out the best way to make sense of incoming terabytes of data has turned into an extreme sport. Likewise, it has become a life-or-death decision in every organization, regardless of their level of maturity, to determine an analytics strategy to harness the potential power of all that data without running the risk of overwhelming teams and paralyzing processes.

Here are five reasons why you should use Integrate.io for Ecommerce data warehouse integration: Typically, Ecommerce data warehouse integration involves several complex steps that even the most advanced data engineer would struggle to execute. You need to build big data pipelines, cleanse data, make sure that data complies with data governance frameworks, and ensure data doesn't get degraded during the process. It's a challenge!

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. In recent years, the term “data lakehouse” was coined to describe this architectural pattern of tabular analytics over data in the data lake.

Building a sales dashboard, but don’t know which KPIs to include? 60+ sales pros share which metrics they track and their favorite sales dashboard types.

Every large enterprise organization is attempting to accelerate their digital transformation strategies to engage with their customers in a more personalized, relevant, and dynamic way. The ability to perform analytics on data as it is created and collected (a.k.a. real-time data streams) and generate immediate insights for faster decision making provides a competitive edge for organizations.

The terms embedded analytics and business intelligence (BI) are often used interchangeably. Both help you find key insights from complex datasets. But are they really the same thing? Is there any major difference between embedded analytics software and a business intelligence platform? In this post, you will find all the details.

Our new feature helps you implement Type 2 slowly changing dimensions for your historical database analytics with no coding needed.