Cloudera Enterprise Data Hub

Ever since I joined my current organization Cloudera Enterprise Data Hub has been a vital solution for data visualization. It offers analytics tools ranging from database, machine learning, data warehouse, and processing in one place.

Cloudera is useful for working with data center architects to optimize the effect of data and uncover its hidden value. Cloudera offers solutions to formalize the enterprise standard database, including data governance, management, and security operations. Cloudera is versatile in terms of combining data management and analytics throughout the lifecycle to collect data where it's needed. Cloudera's adaptability extends to a wide range of scenarios, including security, compliance, migration, and metadata management. By detecting anomalies and reducing cyber dangers, Cloudera helps research customer behavior, churn reduction, and business concerns.

Useful for creating, channeling, and visualizing data from all sectors of the business. It facilitates data collection, campaign management, audience segmentation, predictive analytics, and data cleansing. Supports high-volume processing, data storage, and data visualization. It helps teams automate complicated data pipelines and build data-driven applications while ensuring governance, security, and control throughout the data lifecycle.

We used Cloudera Enterprise for a data lake in order to generate value from big data. Big data stored in the data lake is used for different data science projects like churn prediction, recommendation engines etc.

We used Cloudera to implement our big data service platform. Our team manages a central Hadoop platform where various departments were subscribed in a pay as you go model where they used it to solve various BI and analytical problems. On a day to day basis application teams used it for running Mapreduce/Tez/Spark jobs against their data set which is stored in HDFS.

Quaero’s data management platform (QDMP) and its AdVantage platform are built upon Cloudera’s Distribution of Hadoop (Cloudera Enterprise). The AdVantage platform is targeted for clients in the media industry to better understand their audience, enhance engagement, create richer experiences, and increase overall audience value. Quaero has deployed the platform across several clients in the media industry (ranging in ingestion volume from ~3MM to ~1.5 Billion records per day).

I used it in lab testing. It was a great experience and greatly reduced the configuration/management time.

The ability to monitor and manage numerous Hadoop clusters from one tool. It is an easy way to learn and use REST API and Python client library. It is also easy to use the graphical interface to manage the health of our clusters. It also makes the install process on numerous nodes easy.

I used the Cloudera Enterprise in my previous company wherein I had to used the Cloudera Impala product. I have also used Cloudera Hadoop, Hive, Sqoop, Pig, Mahout etc. Since my project had requirement for trying different tools available in market, we were doing research on which tool is the best, thats where we landed on Cloudera Enterprise products. It is used only in my department. To address the shareholder data in files from different suppliers which needs to be processed via MapReduce framework.

I first worked with Hadoop before there was Cloudera Enterprise. I remember quite well editing files across systems and devising methods to watch for changes, the pain of working out user access privileges, and the search for a sane package management. Cloudera Manager provides tools for all of this and more. The BI engineering team bootstrapped the Hadoop ecosystem, and I have just recently come in to support expansion. Cloudera Enterprise is great, and I appreciate supporting a company like Cloudera which is firmly rooted in the community.

Cloudera was deployed in a internal APJC Lab environment to support Big Data service creation on Company's Unified Server platform. The professional services organization was trying to create services to leverage the server product line services in the region.

I used it at AT&T Interactive for Search Engine analytic department. It is used between product development and the analytics teams