Analytics Vidhya

AUGUST 31, 2022

This article was published as a part of the Data Science Blogathon. Introduction A data lake is a central data repository that allows us to store all of our structured and unstructured data on a large scale. The post A Detailed Introduction on Data Lakes and Delta Lakes appeared first on Analytics Vidhya.

Data Lake 271

Data Lake Unstructured Data Big Data Dashboards 271

Analytics Vidhya

DECEMBER 20, 2022

This article was published as a part of the Data Science Blogathon. Before seeing the practical implementation of the use case, let’s briefly introduce Azure Data Lake Storage Gen2 and the Paramiko module. The post An Overview of Using Azure Data Lake Storage Gen2 appeared first on Analytics Vidhya.

Data Lake 271

Data Lake Big Data Data Science Publishing 271

Analytics Vidhya

DECEMBER 1, 2021

This article was published as a part of the Data Science Blogathon. Image Source: GitHub Table of Contents What is Data Engineering? Components of Data Engineering Object Storage Object Storage MinIO Install Object Storage MinIO Data Lake with Buckets Demo Data Lake Management Conclusion References What is Data Engineering?

Data Lake 391

Data Lake Data Science Publishing Software 391

Analytics Vidhya

JULY 29, 2022

This article was published as a part of the Data Science Blogathon. The post How a Delta Lake is Process with Azure Synapse Analytics appeared first on Analytics Vidhya.

Data Lake 398

Data Lake Data Warehouse Analytics Data Science 398

Analytics Vidhya

OCTOBER 10, 2022

This article was published as a part of the Data Science Blogathon. Introduction Most of you would know the different approaches for building a data and analytics platform. You would have already worked on systems that used traditional warehouses or Hadoop-based data lakes. Selecting one among […].

Data Lake 350

Data Lake Data Science Publishing Analytics 350

Analytics Vidhya

OCTOBER 10, 2022

This article was published as a part of the Data Science Blogathon. Introduction In the modern data world, Lakehouse has become one of the most discussed topics for building a data platform.

Data Lake 358

Data Lake Data Science Publishing Enterprise 358

DataKitchen

DECEMBER 9, 2024

They opted for Snowflake, a cloud-native data platform ideal for SQL-based analysis. The team landed the data in a Data Lake implemented with cloud storage buckets and then loaded into Snowflake, enabling fast access and smooth integrations with analytical tools.

Data Quality 161

Data Quality Data Lake Testing Statistics 161

AWS Big Data

JULY 18, 2024

Over the years, organizations have invested in creating purpose-built, cloud-based data lakes that are siloed from one another. A major challenge is enabling cross-organization discovery and access to data across these multiple data lakes, each built on different technology stacks.

Data Lake 129

Data Lake Publishing Metadata Data-driven 129

AWS Big Data

AUGUST 15, 2024

Unlocking the true value of data often gets impeded by siloed information. Traditional data management—wherein each business unit ingests raw data in separate data lakes or warehouses—hinders visibility and cross-functional analysis. Amazon DataZone natively supports data sharing for Amazon Redshift data assets.

Data Lake 120

Data Lake Data Warehouse Data Governance Publishing 120

AWS Big Data

DECEMBER 17, 2024

Today, Amazon Redshift is used by customers across all industries for a variety of use cases, including data warehouse migration and modernization, near real-time analytics, self-service analytics, data lake analytics, machine learning (ML), and data monetization.

Data Lake 95

Data Lake Data Warehouse Data-driven Optimization 95

AWS Big Data

MARCH 10, 2023

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

Data Lake 122

Data Lake Sales Data Warehouse Snapshot 122

AWS Big Data

OCTOBER 29, 2024

This led to inefficiencies in data governance and access control. AWS Lake Formation is a service that streamlines and centralizes the data lake creation and management process. The Solution: How BMW CDH solved data duplication The CDH is a company-wide data lake built on Amazon Simple Storage Service (Amazon S3).

Data Lake 104

Data Lake Sales Metadata Machine Learning 104

AWS Big Data

JUNE 10, 2024

Use cases for Hive metastore federation for Amazon EMR Hive metastore federation for Amazon EMR is applicable to the following use cases: Governance of Amazon EMR-based data lakes – Producers generate data within their AWS accounts using an Amazon EMR-based data lake supported by EMRFS on Amazon Simple Storage Service (Amazon S3)and HBase.

Data Lake 112

Data Lake Metadata Data Warehouse Data Processing 112

AWS Big Data

DECEMBER 4, 2024

With this new functionality, customers can create up-to-date replicas of their data from applications such as Salesforce, ServiceNow, and Zendesk in an Amazon SageMaker Lakehouse and Amazon Redshift. SageMaker Lakehouse gives you the flexibility to access and query your data in-place with all Apache Iceberg compatible tools and engines.

Data Integration 112

Data Integration Data Lake Statistics Data-driven 112

AWS Big Data

SEPTEMBER 13, 2023

A modern data architecture is an evolutionary architecture pattern designed to integrate a data lake, data warehouse, and purpose-built stores with a unified governance model. The company wanted the ability to continue processing operational data in the secondary Region in the rare event of primary Region failure.

Data Lake 111

Data Lake Data Processing Metadata Snapshot 111

AWS Big Data

DECEMBER 4, 2024

Amazon SageMaker Lakehouse , now generally available, unifies all your data across Amazon Simple Storage Service (Amazon S3) data lakes and Amazon Redshift data warehouses, helping you build powerful analytics and AI/ML applications on a single copy of data. Having confidence in your data is key.

Data Analytics 100

Data Analytics Analytics Data Lake Data Quality 100

AWS Big Data

JANUARY 15, 2025

Plug-and-play integration : A seamless, plug-and-play integration between data producers and consumers should facilitate rapid use of new data sets and enable quick proof of concepts, such as in the data science teams. As part of the required data, CHE data is shared using Amazon DataZone.

IoT 110

IoT Machine Learning Metadata Data-driven 110

AWS Big Data

JUNE 23, 2023

Events and many other security data types are stored in Imperva’s Threat Research Multi-Region data lake. Imperva harnesses data to improve their business outcomes. As part of their solution, they are using Amazon QuickSight to unlock insights from their data.

Data Lake 91

Data Lake Dashboards Cost-Benefit Data Warehouse 91

DataKitchen

AUGUST 19, 2021

Figure 3 shows an example processing architecture with data flowing in from internal and external sources. Each data source is updated on its own schedule, for example, daily, weekly or monthly. The data scientists and analysts have what they need to build analytics for the user. The new Recipes run, and BOOM! Conclusion.

Data Warehouse 246

Data Warehouse Data Lake Manufacturing Testing 246

AWS Big Data

FEBRUARY 26, 2025

Given the diverse data integration needs of customers, AWS offers a robust data integration system through multiple services including Amazon EMR , Amazon Athena , Amazon Managed Workflows for Apache Airflow (Amazon MWAA) , Amazon Managed Streaming for Apache Kafka (MSK) , Amazon Kinesis , and others. and/or its affiliates in the U.S.

Data Integration 96

Data Integration Data Lake Data Warehouse Unstructured Data 96

DataKitchen

NOVEMBER 29, 2021

From our unique vantage point in the evolution toward DataOps automation, we publish an annual prediction of trends that most deeply impact the DataOps enterprise software industry as a whole. For example, a Hub-Spoke architecture could integrate data from a multitude of sources into a data lake.

Testing 245

Testing Data Lake Data Architecture Manufacturing 245

DataKitchen

DECEMBER 7, 2021

This book is not available until January 2022, but considering all the hype around the data mesh, we expect it to be a best seller. In the book, author Zhamak Dehghani reveals that, despite the time, money, and effort poured into them, data warehouses and data lakes fail when applied at the scale and speed of today’s organizations.

Data-driven 246

Data-driven Data Governance Big Data Data Science 246

AWS Big Data

AUGUST 3, 2023

Data analytics on operational data at near-real time is becoming a common need. Due to the exponential growth of data volume, it has become common practice to replace read replicas with data lakes to have better scalability and performance. For more information, see Changing the default settings for your data lake.

Data Lake 97

Data Lake Visualization Dashboards Insurance 97

AWS Big Data

JUNE 19, 2023

Security Lake automatically centralizes security data from cloud, on-premises, and custom sources into a purpose-built data lake stored in your account. With Security Lake, you can get a more complete understanding of your security data across your entire organization.

Publishing 105

Publishing Dashboards Visualization Management 105

DataKitchen

AUGUST 9, 2021

Instead of having a giant, unwieldy data lake , the data mesh breaks up the data and workflow assets into controllable and composable domains with inherent interdependencies. Domains are built from raw data and/or the output of other domains. Figure 5: Domain interfaces as URLs. How does one get access to a domain?

Testing 246

Testing Data Lake Metadata Publishing 246

AWS Big Data

DECEMBER 16, 2024

If you want to revert a draft notebook to its last published state, choose Revert to published version to roll back to the most recently published version. About the Authors Chiho Sugimoto is a Cloud Support Engineer on the AWS Big Data Support team. Now, lets start running queries on your notebook. Choose Run all.

Visualization 87

Visualization Data Processing Testing Publishing 87

AWS Big Data

MARCH 5, 2025

Solution overview This solution provides a streamlined way to enable cross-account data collaboration using Amazon DataZone domain association while maintaining security and governance. Data publishers : Users in producer AWS accounts. Data subscribers : Users in consumer AWS accounts.

Analytics 60

Analytics Publishing Metadata Sales 60

AWS Big Data

DECEMBER 4, 2024

Open table formats are emerging in the rapidly evolving domain of big data management, fundamentally altering the landscape of data storage and analysis. By providing a standardized framework for data representation, open table formats break down data silos, enhance data quality, and accelerate analytics at scale.

Snapshot 84

Snapshot Metadata Data Lake Optimization 84

AWS Big Data

JULY 2, 2024

Fine-grained access control is a crucial aspect of data security for modern data lakes and data warehouses. As organizations handle vast amounts of data across multiple data sources, the need to manage sensitive information has become increasingly important.

Sales 119

Sales Data Lake Publishing Data Warehouse 119

CIO Business Intelligence

JUNE 9, 2022

All this data arrives by the terabyte, and a data management platform can help marketers make sense of it all. Marketing-focused or not, DMPs excel at negotiating with a wide array of databases, data lakes, or data warehouses, ingesting their streams of data and then cleaning, sorting, and unifying the information therein.

Management 144

Management Advertising Data Lake Sales 144

Smart Data Collective

AUGUST 17, 2022

You can safely use an Apache Kafka cluster for seamless data movement from the on-premise hardware solution to the data lake using various cloud services like Amazon’s S3 and others. It is because you usually see Kafka producers publish data or push it towards a Kafka topic so that the application can consume the data.

Data Lake 130

Data Lake Insurance Data-driven Data Processing 130

AWS Big Data

FEBRUARY 26, 2025

Analytics remained one of the key focus areas this year, with significant updates and innovations aimed at helping businesses harness their data more efficiently and accelerate insights. From enhancing data lakes to empowering AI-driven analytics, AWS unveiled new tools and services that are set to shape the future of data and analytics.

Analytics 60

Analytics Data Lake Metadata Data Warehouse 60

AWS Big Data

OCTOBER 10, 2023

Data governance is the process of ensuring the integrity, availability, usability, and security of an organization’s data. Due to the volume, velocity, and variety of data being ingested in data lakes, it can get challenging to develop and maintain policies and procedures to ensure data governance at scale for your data lake.

Data Quality 111

Data Quality Data Governance Data Lake Testing 111

AWS Big Data

JANUARY 31, 2023

We have collected some of the key talks and solutions on data governance, data mesh, and modern data architecture published and presented in AWS re:Invent 2022, and a few data lake solutions built by customers and AWS Partners for easy reference. Starting with Amazon EMR release 6.7.0,

Data Lake 98

Data Lake Data Governance Data Architecture Machine Learning 98

AWS Big Data

JUNE 26, 2024

New feature: Custom AWS service blueprints Previously, Amazon DataZone provided default blueprints that created AWS resources required for data lake, data warehouse, and machine learning use cases. You can build projects and subscribe to both unstructured and structured data assets within the Amazon DataZone portal.

Data Lake 116

Data Lake Data Warehouse Unstructured Data Data Governance 116

DataKitchen

DECEMBER 6, 2022

The two things we are most excited about are: First, DataOps is distinct from all Data Analytic tools. As founders, we sat in a room eight years ago (when all the rage was Hadoop, data prep, and data lakes) and debated — will there ever be an ‘ops’ layer that sits next to all the current data tools?

Software 130

Software Marketing Data Lake Testing 130

Cloudera

APRIL 22, 2021

Apache Ozone is one of the major innovations introduced in CDP, which provides the next generation storage architecture for Big Data applications, where data blocks are organized in storage containers for larger scale and to handle small objects. Cloudera will publish separate blog posts with results of performance benchmarks.

Data Lake 101

Data Lake Cost-Benefit Metadata Big Data 101