Visual Guide to Data Lake Icon and Architecture

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An artist's illustration of artificial intelligence (AI). This image represents storage of collected data in AI. It was created by Wes Cockx as part of the Visualising AI project launched ...
Credit: pexels.com, An artist's illustration of artificial intelligence (AI). This image represents storage of collected data in AI. It was created by Wes Cockx as part of the Visualising AI project launched ...

A data lake icon is a visual representation of a data lake's architecture. It's a simple way to understand the different components that make up a data lake.

A data lake icon typically includes a central repository, which stores raw and unprocessed data. This repository is often depicted as a large container or bucket.

Data ingestion is a key part of a data lake's architecture, and it's usually represented by an arrow pointing into the central repository. This arrow symbolizes the flow of data into the lake.

The data lake icon also often includes a processing layer, which is responsible for transforming and refining the data. This layer is often depicted as a separate box or container.

Data Lake Architecture

Data lake storage has come a long way since the days of three large racks of disk drives needed for just 1TB of data. Today, you can have petabytes of data at your disposal, either physically or virtualized in the cloud.

Credit: youtube.com, Data Lake Architecture

To manage this complexity, it's essential to know what you have in your data lake, which is where catalogs come in – think of them like a library card system that quickly defines each piece of data, its source, date of acquisition, and other attributes.

A good data lake architecture should also include audit software and active governance to ensure that data is handled correctly. This means knowing why you have the data, how you have it, and when you can delete it.

To give you a better idea, here are some key considerations for a modern data lake storage architecture:

  • Use catalogs to know what you have and simplify data queries and archival.
  • Implement audit software and active governance to handle data correctly.
  • Use Access Control Lists (ACL) and other security practices to govern data access.
  • Encrypt data as part of its initial intake, and ensure that security tokens are stored and managed properly.

Modern Architecture

Modern Architecture is all about simplifying the complex world of data storage. Historically, designing and managing data storage has been the most costly and challenging aspect of IT.

Twenty-five years ago, 1TB of data storage required three large racks of disk drives, each the size of a small washing machine, making it a massive undertaking. Today, data lake storage provides the opportunity to have petabytes of data at your disposal.

Credit: youtube.com, What is a Data Architecture? Modern Data Architectures Explained

To make the most of modern data lake storage, it's essential to know what you have. This can be achieved by using a combination of catalogs, similar to a library card system, to quickly define each piece of data within the lake, its source, date of acquisition, and other attributes.

Data catalogs help simplify data queries and archival, making it easier to find what you need when you need it. This is a game-changer for organizations that deal with vast amounts of data.

To ensure data security and management, audit software and active governance are crucial. This involves tracking what data you have, why you have it, how you have it, where you acquired it, and who can access it.

Access Control Lists (ACL) and other security practices are designed and governed for each data lake. This is a critical step in protecting sensitive data and preventing unauthorized access.

Cloud data lakes encrypt data as part of their initial intake, providing an extra layer of security. However, this requires specialized software skills and changes to applications and service designs.

Here are the best practices for modern data lake storage architecture:

  • Use catalogs to know what you have and simplify data queries and archival.
  • Implement audit software and active governance to track data security and management.
  • Design and govern Access Control Lists (ACL) and other security practices for each data lake.
  • Take advantage of cloud data lake encryption to protect sensitive data.

Stock Illustrations

Credit: youtube.com, What is a Data Lake?

Stock illustrations can be a great way to visualize data lake concepts. Browse 440+ data lake icon stock illustrations and vector graphics available royalty-free, or start a new search to explore more great stock images and vector art.

Data lake icon sets offer a variety of illustrations. Data lake icon set. Data storage, data strategy line illustration. Structured and unstructured data. Editable Stroke

You can find data lake icons in different styles and formats. Big data, data, analyzing, database, icon, icon set, data center, data mining, business, finance, financial report, pie chart, chart, graph

Data lake icons often include artificial intelligence and machine learning elements. Data, big data, analyzing, artificial intelligence, machine learning, icon, icon set, editable stroke, outline, computer chip, automated, diagram, technology, business, data center, finance, global business, cloud computing

Some data lake icon sets feature a data center or network server theme. Data center, data, network server, database, icon, icon set, serverless computing, big data, computer chip, server room, computer network, web page, CPU, technology

Data lake icons can also be found in RGB color and black silhouette formats. Data Lake Icon Set. Black Silhouette. The set contains icons as Big Data, Pattern, Database, Three Dimensional, Personal Data

Desiree Feest

Senior Assigning Editor

Desiree Feest is an accomplished Assigning Editor with a passion for uncovering the latest trends and innovations in technology. With a keen eye for detail and a knack for identifying emerging stories, Desiree has successfully curated content across various article categories. Her expertise spans the realm of Azure, where she has covered topics such as Azure Data Studio and Azure Tools and Software.

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