Get more value from your data lake

An enterprise data lake can provide numerous benefits that a traditional data warehouse cannot. And, when these benefits are coupled with a cloud-native ETL product like Matillion ETL to help move your data from your data lake to your cloud data warehouse, the advantages become even greater.

Store data in its native format

Data can be stored more quickly and easily because it no longer needs to go through an initial transformation process.

Increase access to your data

Increase agility and provide greater opportunities for data exploration and proof of concept initiatives for data scientists, engineers and analysts.

Maintain security

Apply permission-based privacy and security policies to data lake environments ensuring the right people have access to individual data lakes.

Achieve greater data customization

Data lakes allow the schema to be developed and tailored on a case-by-case basis rather than defining the schema for the data upfront, giving you more flexibility to innovate and process data as needed.

Decouple storage and compute

Optimize your costs by tailoring your data storage requirements to frequency of access and remove any compute-related costs.

Streamline data preparation

Perform powerful transformations in less time by skipping over the intermediate step of having to run transformations prior to loading your data into the data lake.

Achieve greater scalability

Data lakes are designed to handle growing volumes and varieties of data at any given velocity, making them highly scalable.

Increase agility

Introduce new use cases without having to re-engineer your architecture, making it faster and simpler to innovate new use cases for your data.

Locate and curate data

Keep track of what data you have, who has access to it, and what it’s being used for with a centralized data lake.


Realize a single source of data truth

A key value proposition of data lakes is the ability to store data from diverse source systems – such as structured, semistructured, and unstructured formats – at a very low cost. This enables organizations to not only store a lot more data than they might have otherwise but to have access to this data when potential use cases for such data arise.

Both cloud data lakes and cloud data warehouses are hosted in the cloud and used for storing large volumes of data, but that’s where the similarities end. A cloud data lake is a raw pool of data for which the purpose of has yet to be defined while a cloud data warehouse stores structured, transformed data that has already been processed for a specific use. Often, organizations need both – a data lake to corral big data cost effectively and a cloud data warehouse to prepare data for analytics use by business users.

Managing data lakes to avoid data silos

With such large amounts of raw structured, semi-structured, and unstructured data being stored in one repository, there is a risk of the data lake becoming a collection of disconnected data pools or information silos. To mitigate these risks, data must:

  • Be cataloged in a way that allows you to identify what data you have and where it is stored
  • Have a lineage so you know where the data has come from and what has happened to it
  • Be accurate and fit for a purpose or use case
  • Be protected from unauthorized access

Make your data lake an innovation engine

The greatest value of a data lake is the ability for organizations to use it as an engine for innovation. By making data access simpler, faster, and more efficient for users and facilitating experimentation with different processing technologies, businesses can discover game-changing insights that fuel competitive advantage.

Connect your data lake to your cloud data warehouse with Matillion

Data lakes can be an important part of an enterprise data management strategy. Because of its purpose as a single repository, a data lake is also best served by including an ETL solution, like Matillion, that can extract data from the data lake and then load that data into the cloud data warehouse where transformation can occur.

Matillion can also enable you to move data back into a data lake (Amazon S3), helping you derive greater value in less time from the data being stored in your data lake.

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Essential guide to data lakes
Ebook

Essential guide to data lakes

Data lakes can handle the variety, volume, and velocity of modern data workloads and provide a cost-effective way to scale, store and access structured, semi-structured, and unstructured data types. Learn more about how to effectively use a data lake to optimize your data analytic efforts.

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