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.

• Regulatory compliance capabilities on Cloudera Enterprise Data Hub makes it effective to protect our day-to-day business activities.
• Risk modeling and analytics tools.
• Fraud detection and cybersecurity capabilities.
• Marketing automation capabilities.

• It makes it easy to manage the entire data lifecycle by infusing AI.
• Data analysis enables us to make informed decisions.
• In-memory high speed data processing which requires zero manual procedures.
• Cloudera simplify data management by automating the entire procedure.

Vertica

BigTime Software, ThoughtFarmer

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.

• Cloudera provides excellent expert support to optimize all levels of the organizational data storage process.
• By developing and executing your options for scaling in various parts of the business, Cloudera provides advice, technical and practical knowledge.

• Cloudera improves data management by leveraging the organization's data processing and analysis capabilities.
• Cloudera is competitive by bringing the simplicity of data management to the most important areas of the business.
• Cloudera manages the lifecycle of enterprise data, from the edge to AI, in any cloud or data center.
• Cloudera offers options to optimize and understand complicated scenarios, make profitable judgments, generate results, and assess business performance.
• Cloudera is useful for performing complex analysis on large amounts of data.
• Cloudera is an excellent option for turning data into a strategic asset.
• Cloudera provides control tools to manage high-speed data processing and compromise.

MongoDB, Teradata Aster Database and Clearsense

IBM Netezza Performance Server, Clearsense, Panoply

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.

• Using real-time data, Cloudera is ideal for managing marketing operations, automation, audience targeting, churn prevention, and customer retention.
• Cloudera enables hybrid deployments, to take advantage of deployment flexibility and accessibility to work with data from any location.

• Cloudera provides visibility throughout the data lifecycle.
• Due to its open architecture, it allows modification.
• It can be used to make data-driven business decisions that increase efficiency, minimize risk, and provide new insights.
• Reduce costly data silos by performing many data analysis operations on the same data at the same time, directly at the source.

Panoply, Actian Avalanche and Cyral

Firebolt, Panoply, Cyral

• The tools in Cloudera Enterprise have enabled us to perform seamless upgrades and monitor the clusters
• Investing in the support enables us to engage with Cloudera to get access to required patches and backports in case of bugs which helps with wider adoption of open source software in the enterprise.
• Voice of the customer enabled us to put forth requests for new features across various components.

• Reduces costs to store data.
• Enable data science use cases that generates revenue.

Hortonworks Data Platform

Apache Spark, Hortonworks Data Platform, Kubernetes, Docker