AWS Lake Formation to provide partners and customers with simplified means of aggregating and analyzing vast volumes of data
True business analytics and “Big Data” require vast volumes of data from disparate sources. Amazon Web Services is looking to make Big Data easier for enterprise customers through AWS Lake Formation, a full managed service that provides partners and customers with a simplified means to build, secure, and manage data lakes.
The Lowdown: AWS, the cloud division of Amazon, says Lake Formation automates the process for collecting, normalizing, and cataloging data through pre-defined templates. Automation simplifies the process of making data collected from a variety of sources across an enterprise ready for data mining and analytics.
The Details: In addition, AWS will enable partners and customers to use a variety of analytics and machine learning tools to parse and analyze collected data. The applications include Amazon Redshift, Amazon Athena, and AWS Glue, with Amazon EMR, Amazon QuickSight, and Amazon SageMaker.
AWS Lake Formation is built on Amazon S3, the cloud storage service. Lake Formation comes at no additional cost; partners and customers pay only for the underlying cloud service.
The Impact: Through Lake Formation, AWS is attempting to solve one of the thorniest problems in Big Data and analytics: normalization. Businesses struggle to collect and rationalize data from across their different systems. By creating the managed service, automated processes, and organizational templates, AWS believes it can help its cloud partners and customers build more effective Big Data resources expeditiously.
The Buzz: “Our customers tell us that Amazon S3 is the ideal place to house their data lakes, which is why AWS hosts more data lakes than anyone else – with tens of thousands and growing every day. They’ve also told us that they want it to be easier and faster to set up and manage their data lakes,” said Raju Gulabani, vice president of databases, analytics, and machine learning at AWS. “That’s why we built AWS Lake Formation, so customers can spend more time learning from their data and innovating, rather than wrestling that data into functioning data lakes. AWS Lake Formation is available today, and we’re excited to see how customers use it as one of the building blocks for growing and transforming their businesses and customer experiences.”
“I focus on helping clients in their ‘Data on Cloud’ journey. Specific to that, we have seen that organizations are dealing with a lack of trusted data when they need to perform analytics on data coming from multiple sources,” said Namrata Maheshwary, senior architect for the Data Business Group at Accenture. “Data cleansing is a critical step in data analytics and can greatly impact the business outcome and decision-making. The new features in AWS Lake Formation have been hugely beneficial to address the challenge of data veracity and securing access to the data lake. We found it tremendously useful to make use of the advanced machine learning techniques for data preparation to find matching records, and to clean and deduplicate data from different data sources. This will help reduce the time, effort, and cost, while improving the quality and accuracy of the data in a customer’s data lakes.”
“AWS Lake Formation allows us to deliver a secure data lake with access to relevant data in days,” said Arnav Gupta, AWS practice lead at Quantiphi, an AI and Big Data software and services company. “We now have the ability to deliver the best of both worlds for our customers – full security, plus simplified access to relevant data for their users to make decisions easily. Our customers can focus on making smarter, analysis-driven business decisions by tapping into a powerful, centralized data source.”