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Quaero's data management platform, powered by Cloudera Enterprise, offers a comprehensive solution for businesses in the media industry. …
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What is Cloudera Enterprise Data Hub?
The Cloudera Enterprise Data Hub powered by SDX is a multifunction analytics solution that supports a range of operational and analytic use cases for enterprises.
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What is Cloudera Enterprise Data Hub?
The Cloudera Enterprise Data Hub powered by SDX is a multifunction analytics solution that supports a range of operational and analytic use cases for enterprises.
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Quaero's data management platform, powered by Cloudera Enterprise, offers a comprehensive solution for businesses in the media industry. Its versatility, robust features, and adaptability make it a valuable asset for optimizing data and uncovering hidden insights. Cloudera Enterprise has proven instrumental in various use cases, including research on customer behavior, churn reduction, and cybersecurity measures. By detecting anomalies and reducing cyber dangers, Cloudera helps businesses safeguard their operations. The platform also facilitates critical processes like data collection, campaign management, audience segmentation, predictive analytics, and data cleansing.
Cloudera Enterprise's scalability is particularly noteworthy, enabling businesses to handle large datasets effectively. With its high-volume processing capabilities, efficient data storage, and powerful visualization tools, teams can automate complex data pipelines and build data-driven applications while maintaining governance, security, and control throughout the entire data lifecycle. Customers appreciate the comprehensive set of tools provided by Cloudera Manager for simplified administrative tasks such as file editing across systems, user access privilege management, and package management, enhancing productivity within organizations.
Real-world use cases of Cloudera Enterprise span across different industries, including successful deployments in the Search Engine analytic department at AT&T Interactive and the creation of Big Data services on unified server platforms. Cloudera Enterprise offers flexibility in running Mapreduce/Tez/Spark jobs against large datasets stored in HDFS through a pay-as-you-go model. It serves as a central hub for generating value from big data by acting as a data lake, fueling data science projects such as churn prediction and recommendation engines. In lab testing environments, Cloudera Enterprise has significantly reduced configuration and management time, streamlining processes. With its intuitive graphical interface, Cloudera Enterprise simplifies administrative tasks and enhances the overall user experience.
Excellent Management Capabilities: Many users have praised Cloudera Manager for its excellent management capabilities, making it easy to effectively manage a Hadoop cluster. They appreciate the user-friendly interface and robust features that allow them to efficiently monitor and control their cluster's performance, resource allocation, and configuration.
Comprehensive Solution: Several reviewers appreciate that Cloudera provides all the necessary components to build a data hub, making it a comprehensive solution for their needs. With Cloudera, they can seamlessly integrate different tools and technologies required for data processing, storage, and analysis. This eliminates the need for piecemeal solutions and simplifies the overall setup and maintenance of their infrastructure.
Data Discovery and Automation: Users have mentioned that Cloudera helps them discover data across workloads and enables them to automate workflows. Some users specifically mention customer experience and marketing automation as areas where Cloudera excels in automating processes. They highlight how these capabilities enhance efficiency by reducing manual efforts in data exploration and streamlining repetitive tasks. This empowers businesses to harness the full potential of their data while saving time and resources.
Challenging customization: Some users have found it challenging to customize certain features of Cloudera due to inadequate documentation and a lack of informative resources for newcomers. They have expressed frustration in trying to understand how to modify these features without clear instructions or guidance.
Expensive membership fees: Several reviewers have mentioned that they find Cloudera's membership fees to be expensive, suggesting that they could be more profitable compared to other competing technologies. This has led some users to question the value they are receiving for the price they pay.
Lack of knowledgeable resources: Users in the APJC region have expressed difficulty in finding resources knowledgeable in Cloudera solutions for Lab and PoC activities, highlighting a need for improved support in this area. They feel that there is a shortage of experts who can provide assistance and guidance when dealing with complex issues or specific use cases.
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Reviews
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April 02, 2022
My Insight for 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.
- It is an integrated suite with all analytics engines in one place.
- Help discover data across workloads.
- Grow business by automating workflow: customer experience and marketing automation.
- Protect business through risk modeling and analysis.
- For newbies, it can be challenging to customize some features since there’s not enough documentation.
- Improve on version control.
- 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.
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 enables the use of options to automate, build, and deploy machine learning and artificial intelligence.
- Cloudera helps build the self-service machine learning workflow by providing technologies that make data science easy.
- Some of Cloudera's documentation is not accurate or informative enough for newcomers.
- In terms of membership pricing, I would like Cloudera to be more profitable.
- 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.
Cloudera is a
great choice because it provides fast streaming data for tracking, breaks down
silos by providing unified self-service platforms for data-driven insights,
secures machine learning, AI solutions, and stores self-service data, enabling
our analysts to concentrate on more important tasks like displaying critical
information.
March 11, 2022
In order to improve analysis and data management.
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.
- Cloudera excels at consolidating existing data clusters without interfering with application performance.
- Cloudera simplifies operations by providing separate compute containers that can be individually configured or upgraded based on the needs of each department in a common cluster.
- Cloudera membership fees are expensive; I think they could be more profitable than competing technologies.
- 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.
Cloudera is
compatible with Windows operating systems, and Mac allows cloud-based
deployment, it is also very useful to configure data encryption, guarantee
protocols, and security policies. It also provides integrated auditing and
monitoring capabilities, as well as a control comprehensive data repository for
the enterprise, and ensures vendor compatibility through its open-source
architecture.
December 18, 2017
Cloudera Enterprise Review
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.
- Stability
- Support
- Documentation
- More Up to date technologies(e.g. Spark 2.2)
- Data Science Workbench improvement
- Data quality tools
- Reduces costs to store data.
- Enable data science use cases that generates revenue.
Cloudera supports Impala and Hortonworks supports LLAP and both of them are good in terms of performance. Hortonworks uses more up to date technology support in terms of supported versions.
July 19, 2017
A brief Cloudera Review
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.
- One of the oldest distributors of enterprise standard Hadoop.
- Distribution is based on open source Hadoop even though customizations are done on top of that.
- Faster updates and bug fixes to the products as they have Apache committers.
- Central configuration and control of your Hadoop platform (but still needs improvements).
- Not fully Open Source, couple of components of the distributions are privately owned, meaning with public contributions are not welcome
- Improvements to Cloudera manager can only be recommended. its very hard to get it done once recommended as the full control is with them.
- Should make components more aligned to Open Source rather than making it closed sourced.
- Custom Features of open source software tools supported only by Cloudera are tricky. Cant commit changes to tools like Hue.
- Improvements to Cluster Management tool is required, which are already available to its competitors.
- Improvements request would take a while.
- Fast bug fixes and stability in releases are great.
- Migration to other platforms would not be that easy if you start using proprietary tools.
It was the first and best Hadoop distribution when we started years ago. But the situation changed now and if given a choice, may end up choosing something else.