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.

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.

Qlik enhances analytics exploration in Snowflake by launching Direct Query, a new capability that allows Qlik Sense applications and dashboards to query Snowflake directly using SQL pushdown.

Snowflake has once again transformed data management and data analytics with our newest workload—Unistore. For decades, transactional and analytical data have remained separate, significantly limiting how fast organizations could evolve their businesses. With Unistore, organizations can use a single, unified data set to develop and deploy applications, and analyze both transactional and analytical data together in near-real time.

Geospatial data has many uses outside of traditional mapping, such as site selection and land intelligence. Accordingly, many businesses are finding ways to incorporate geospatial data into their data warehouses and analytics. Google Earth Engine and BigQuery are both tools on Google Cloud Platform that allow you to interpret, analyze, and visualize geospatial data.

We are excited to announce that Cloudera is named as a 2022 Gartner Peer Insights Customers’ Choice for Cloud Database Management Systems (DBMS). Peer Insights is a user review site, the technology professional’s “go-to” destination for information on customer experience. Gartner Peer Insights collects anonymous customer reviews on select product categories. To date, Gartner has collected over 450,000 reviews for 18,000 products in over 425 categories.

Businesses in every sector confront data roadblocks. Accessing, harnessing and analyzing such a vast quantity of complex information is a tall order, if you're not prepared. It is essential to build a strategy and pick the right solution to handle your business-critical data if you are to assist your customers, end-users and partners in being able to leverage it to the fullest. Will data be your company's weakness, or competitive edge?

Here at Cloudera, we’re committed to helping make the lives of data practitioners as painless as possible. For data scientists, we continue to provide new Applied Machine Learning Prototypes (AMPs), which are open source and available on GitHub. These pre-built reference examples are complete end-to-end data science projects. In Cloudera Machine Learning (CML), you can deploy them with the single click of a button, bringing data scientists that much closer to providing value.

In the first blog of the Universal Data Distribution blog series, we discussed the emerging need within enterprise organizations to take control of their data flows. From origin through all points of consumption both on-prem and in the cloud, all data flows need to be controlled in a simple, secure, universal, scalable, and cost-effective way.