Merit data architects have successfully implemented Cloudera for several clients that have needed a solution for hybrid data management. In this blog, we will discuss the benefits of Cloudera especially in organisations that have several data sources and decision-makers that struggle to access relevant data with ease.
- Cloudera offers a modern data platform for seamless and secure data management across both private and public cloud infrastructure.
- It is an ideal solution to consider for companies that want to unify data from on-premise infrastructure, private cloud and public cloud.
- For decision-makers and business leaders, the technology solution used is secondary. They want to solve a business problem to drive financial outcomes and customer delight. In the case of Cloudera, the problem solved revolves around how to make it easier to leverage data from numerous data stores to feed into BI and analytics engines. It helps decision-makers access data better and derive insights faster.
The 2020 winner of Cloudera’s Data Impact award – Global Telecom – was grappling with a business problem. It offers a wide-range of telecommunication services including broadband, fixed-line, data cards and value-added services to consumers.
However, their customers were using more and more of their data (3G, 4G and 5G) services, but this additional usage wasn’t translating into revenue. In fact, it was a double whammy of sorts — wherein the company’s operating costs were going up due to greater usage of its telecom infrastructure.
Yet, the company had this large user base and a massive amount of data on them and how these users were using its services. The problem to be solved revolved around monetization.
The company’s senior team determined that the company needed a better way to engage with its customer base, offer new products, bundle together multiple offerings and offer it as a package.
The top-level directive was to invest in “data crunching” and look into their existing data (according to the company’s CIO, this ran to 600 petabytes in 2017) and analyse this data to deliver contextual advertisements.
The brainstorming team which including both technology, data and business leaders hit a bottleneck: Data analytics to draw insights would help but data was stored in many different places. Some in the private cloud, some in the CRM and data about infrastructure and data bandwidth capabilities was stored in a legacy on-premise data warehouse.
The answer revolved around finding a hybrid data platform, one that could seamlessly bring all silos together. After analysing several options, the company decided to implement the Cloudera Data Platform on AWS, to modernise data management workflows.
This helped the company manage its data, interpret analytics, and leverage those insights for improved customer segmentation. This was the starting point of using customer data intelligence better to drive revenue growth and spot new opportunities.
This was possible because Cloudera enabled the ingestion of large volumes of real-time, granular network signal data and integrated it with batch loads from enterprise systems such as billing, payments, etc.
Cloudera – A Hybrid Data Platform
Cloudera Data Platform (CDP) is a modern hybrid data cloud solution that enables the management and security of the end-to-end data lifecycle across all major public and private clouds and also connects seamlessly with on-premises environments.
In 2008, Cloudera was created as a collaboration between Facebook, Google, Oracle, and Yahoo to create a solution that can help businesses leverage Hadoop distribution software. Cloudera Data Platform ensures speed and agility while providing businesses with:
- Scalability, flexibility and cost-efficiency
- Centralisation of data
- Workload optimization for built-on analytics and machine learning
- Providing visibility into data lineage across any cloud and transient clusters
- Allowing a “single pane of glass” to be used across hybrid and multi-clouds
- Improved security and governance
The CDP is available in two versions, the Public Cloud and the Private Cloud.
CDP Public Cloud
A Platform-as-a-Service (PaaS) solution, the CDP Public cloud can work with any cloud provider across locations and easily transfer data workloads from any source to any destination.
The services it offers include:
According to a data intelligence expert at Merit, “Cloudera allows automatic scaling of workloads and resources based on the need for optimal performance and costs. The all-in-one Data Engineering toolkit from Cloudera built on Apache Spark enables orchestration and automation with Apache Airflow for streamlining ETL processes across enterprise analytics teams.”
This facilitates monitoring of highly-developed pipelines and visual debugging using its extensive management tools. Workload environments are isolated and containerised, making them scalable and easy to transport.
From the Edge to AI, the CDP Data Hub service facilitates high-value analytics. Some of its many analytical tasks in a wide range of workloads include streaming, ETL, management of databases/data marts and Machine Learning.
BI analysts can experience cloud-native self-service analytics with CDP Data Warehouse. A unified framework enables securing and governing organisational data and metadata on the hybrid cloud. Data engineering, Streaming and Machine Learning (ML) analytics are integrated within the CDP Data Warehouse.
CDP Machine Learning uses native and comprehensive tools to optimise ML workflows by deploying, serving and monitoring models. The expanded Cloudera Shared Data Experience (SDX) for models enables regulating and automating model categorisation. The findings can be easily transferred for collaboration via CDP experiences including Operational Database and Data Warehouse.
Cloudera Data Visualisation allows users to model data in the virtual data warehouse without removing or updating the underlying data structures or tables. Users do not have to query large amounts of data, making them time and cost-efficient.
Cloudera Operational Database, a managed solution, facilitates the summarisation of the underlying cluster instance as a database. This enables the automatic scaling depending on the workload use of the cluster. It can improve performance within the same infrastructure footprint while automatically resolving operational issues.
CDP Private Cloud
CDP Private Cloud is built for hybrid cloud deployment and connects on-premise environments to public clouds with consistent and integrated security and governance. By decoupling computing and storage, the CDP Private Cloud facilitates independent scaling of clusters.
Cloudera Shared Data Experience (SDX), available on a CDP Private Cloud Base cluster, ensures security, governance and metadata management. The Management Console enables scaling up (or scaling down) of Cloudera Data Warehousing and Cloudera Machine Learning services based on need.
The CDP Private Cloud services include the following:
Machine Learning and Data Warehouse services are similar to those available in the CDP Public Cloud. In addition to these, its collection of analytic engines supports traditional workloads by covering streaming, data marts, Data Engineering, operational database management, and data science processes.
Additionally, Cloudera allows detailed audits and lineage tracing to identify the source of data and its relevance.
Merit Group’s expertise in Hybrid Data Clouds
Merit Group partner with some of the world’s leading B2B intelligence companies within the publishing, automotive, healthcare and retail industries. Our data and engineering teams work closely with our clients to build data products and business intelligence tools that optimise business for growth.
Our data engineers can help you with faster time-to-insights using the Cloudera Data Platform, especially when one is looking for a solution around managing data from public cloud, private cloud and on-premise data sources. This is often the case at large enterprises that retain their legacy infrastructure and added modern cloud-based infrastructure for BI and other analytics or machine learning requirements.
Our data experts consult closelu with our clients’ CIOs and technology decision-makers to choose the hybrid data platform that will be support budgets, project timelines and other specific requirements.
If you’d like to learn more about our service offerings or speak to a data science expert, please contact us here: https://www.meritdata-tech.com/contact-us
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