What is a data lake?

A data lake is one or more centralized repositories for storage of structured and unstructured data at scale to enable effective access for all identified business users, analysts, and data scientists. Data lakes also enable these users to store supplemental data as-is without having to first structure that data to run different types of analytics. 

Data lakes are not designed for a single use case but can best be thought of as a common storage point for related data within an organization. Data stored in a data lake has been delivered without intentional design, leaving it more open for more differentiated use cases such as big data analytics or machine learning in the future.

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What is the difference between a data lake and a data warehouse?

An enterprise data warehouse (EDW) stores data from transactional and business applications in a normalized relational structure intended for standardized access, queries, and reporting. Data is transformed from their sources into these pre-determined structures and schemas for common use cases, such as operational analysis and reporting, serving as a “single source of truth” for users. 

In a data lake, data schemas and structures are not predefined when data is captured. Instead of conforming to specific data types, data lakes provide a blank slate for new types of analytics and data science. For example, data lakes allow data scientists to apply machine learning techniques to alternative forms of data such as log files, clickstreams, and data from social media and Internet of Things (IoT) devices. 

What can a data lake do for my organization?

A data lake provides flexibility for your organization to address new and emerging use cases. 

As an alternative paradigm for data management and storage, data lakes allow users to harness more data from a wider variety of sources without the need for pre-processing and data transformation in advance. With increased data availability, data lakes empower users to analyze data in new ways, helping them find additional insights and efficiencies.

How Precisely can help you build the best data lake

Build your data lake in the cloud with Connect to ensure that your most critical enterprise data is delivered in a timely fashion to your data lake so that it is always fresh with the latest data changes. 

Precisely's data cleansing, matching, and enrichment tools can improve the quality of data in your data lake, so that the it is trusted for your subsequent analytics and data science initiatives.