What is a data lake?

Data lakes are next-generation hybrid data management solutions that can meet big data challenges and drive new levels of real-time analytics. Their highly scalable environment supports extremely large data volumes, accepting data in its native format from a variety of data sources. As a compliment to your data warehouse, they provide the framework for machine learning and real-time advanced analytics in a collaborative environment.  

IBM, in partnership with Cloudera, offers enterprise-grade products and services to help you build a data lake and then manage, govern, access and explore big data. These solutions combine cost-effective, enterprise-grade open source technology with real-time analytic capabilities. Tap into the tremendous potential of previously unanalyzed data and make smarter, more agile, data-driven decisions.

More data management capabilities

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Solutions to optimize the potential of a data lake

Choose from compute and storage options designed to support AI and big data

IBM Power Systems

Increase compute and storage efficiency and maximize performance when building out your Hadoop data lake.

Data storage

Optimize your storage capacity and protect, secure and efficiently move data in your hybrid environment.

Accelerate results and improve accuracy with a well-governed data lake

IBM and Cloudera Hadoop distribution

Optimize the platform of your data lake using an industry-leading, enterprise-grade Hadoop distribution offered by IBM and Cloudera.

Data lake governance

Ensure the integrity of your data lake using proven governance solutions that drive better data integration, quality and security.

Use proven tools that bring speed, AI and machine learning to your big data analytics

IBM Db2 Big SQL

Use an enterprise-grade, hybrid, ANSI-compliant SQL on Hadoop engine to gain massively parallel processing (MPP) and advanced data query.

IBM Big Replicate

Replicate data as it streams into your data lake – so files don’t need to be fully written or closed before transfer.

IBM Watson® Studio

Build and train AI and machine learning models, plus prepare and analyze data — all in a flexible hybrid cloud environment.

Data lake industry use cases

Retail

  • Determine what a customer is likely to purchase online and provide recommendations
  • Identify a customer’s “path to purchase” to understand buying patterns and conduct micro-targeted marketing
  • Predict or proactively identify fraudulent activity from both inside and outside the organization

Banking

  • Predict the success or failure of discounts
  • Pinpoint the “next product to buy” and promote that product to customers
  • Identify which customers are likely to decrease their bank business and employ proactive marketing activities

Hospitality and travel

  • Track and predict customer preferences to guide proactive selling
  • Improve the customer experience and boost brand loyalty through customization and personalization
  • Conduct real-time pricing and analysis

 

“ Using Big SQL as our core engine gave us confidence that we’d be able to succeed with a Hadoop data lake as an enterprise platform. ”

— Raj Ramani, Director of Information Management, Deloitte Canada

   

Resources on data lakes

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Learn about the IBM products, solutions and services available to help you build and grow a successful data lake.