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.

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Data Lake Data Processing Metadata Snapshot 89

AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. In this post, we describe Orca’s journey building a transactional data lake using Amazon Simple Storage Service (Amazon S3), Apache Iceberg, and AWS Analytics.

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Data Lake Analytics Snapshot Optimization 86

AWS Big Data

MAY 24, 2023

When you build your transactional data lake using Apache Iceberg to solve your functional use cases, you need to focus on operational use cases for your S3 data lake to optimize the production environment. availability. The examples are run on a Jupyter Notebook environment attached to the EMR cluster.

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Data Lake Snapshot Metadata Optimization 83

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.

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Data Lake Sales Data Warehouse Snapshot 100

AWS Big Data

MARCH 4, 2024

As enterprises collect increasing amounts of data from various sources, the structure and organization of that data often need to change over time to meet evolving analytical needs. Schema evolution enables adding, deleting, renaming, or modifying columns without needing to rewrite existing data.

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Snapshot Data Lake Metadata Recreation/Entertainment 110

AWS Big Data

FEBRUARY 24, 2023

Data lakes are a popular choice for today’s organizations to store their data around their business activities. As a best practice of a data lake design, data should be immutable once stored. A data lake built on AWS uses Amazon Simple Storage Service (Amazon S3) as its primary storage environment.

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Data Lake Metadata Testing Data Warehouse 82

CIO Business Intelligence

APRIL 25, 2024

“The challenge that a lot of our customers have is that requires you to copy that data, store it in Salesforce; you have to create a place to store it; you have to create an object or field in which to store it; and then you have to maintain that pipeline of data synchronization and make sure that data is updated,” Carlson said.

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Data Integration Data Lake Metadata Data Warehouse 85

AWS Big Data

JANUARY 27, 2023

The AWS Glue Data Catalog provides a uniform repository where disparate systems can store and find metadata to keep track of data in data silos. Apache Flink is a widely used data processing engine for scalable streaming ETL, analytics, and event-driven applications. Apache Hudi also has its own catalog management.

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Data Lake Metadata Business Analysis Data-driven 61

AWS Big Data

AUGUST 1, 2023

In the world of software engineering and development, organizations use project management tools like Atlassian Jira Cloud. Managing projects with Jira leads to rich datasets, which can provide historical and predictive insights about project and development efforts. An AWS account and a login with access to the AWS Management Console.

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Data Lake Data Transformation Cost-Benefit Data-driven 84

AWS Big Data

JANUARY 18, 2024

AWS Lake Formation and the AWS Glue Data Catalog form an integral part of a data governance solution for data lakes built on Amazon Simple Storage Service (Amazon S3) with multiple AWS analytics services integrating with them. In 2022 , we talked about the enhancements we had done to these services.

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Data Lake Metadata Data Governance Statistics 88

AWS Big Data

JUNE 15, 2023

In today’s world, customers manage vast amounts of data in their Amazon Simple Storage Service (Amazon S3) data lakes, which requires convoluted data pipelines to continuously understand the changes in the data layout and make them available to consuming systems. Choose Next.

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Data Lake Metadata Cost-Benefit Management 86

Ontotext

APRIL 10, 2024

Data ecosystems have become jungles and in spite of all the technology, data teams are struggling to create a modern data experience. In most enterprises data teams lack a data map and data asset inventory and are often unaware of data that exists across the organization, its associated profile, quality and associated metadata.

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Metadata Data Lake Data Warehouse Data Quality 52

AWS Big Data

JULY 21, 2023

Data-driven organizations treat data as an asset and use it across different lines of business (LOBs) to drive timely insights and better business decisions. This leads to having data across many instances of data warehouses and data lakes using a modern data architecture in separate AWS accounts.

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Data Lake Data Warehouse Marketing Management 85

Alation

FEBRUARY 13, 2020

In an earlier blog, I defined a data catalog as “a collection of metadata, combined with data management and search tools, that helps analysts and other data users to find the data that they need, serves as an inventory of available data, and provides information to evaluate fitness data for intended uses.”.

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Metadata Management Data Lake Data Governance 52

AWS Big Data

FEBRUARY 6, 2023

For data lake customers who need to discover petabytes of data, AWS Glue crawlers are a popular way to discover and catalog data in the background. This allows users to search and find relevant data from multiple data sources. Choose the table to view the schema and other metadata.

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Metadata Data Lake Machine Learning Management 73

AWS Big Data

JUNE 7, 2023

Cargotec captures terabytes of IoT telemetry data from their machinery operated by numerous customers across the globe. This data needs to be ingested into a data lake, transformed, and made available for analytics, machine learning (ML), and visualization. The target accounts read data from the source account S3 buckets.

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Metadata Data Lake Machine Learning Big Data 55

AWS Big Data

FEBRUARY 23, 2023

Data lakes provide a centralized repository that consolidates your data at scale and makes it available for different kinds of analytics. AWS Glue crawlers are a popular way to scan data in a data lake, classify it, extract schema information from it, and store the metadata automatically in the AWS Glue Data Catalog.

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Data Lake Management Metadata Big Data 77

BizAcuity

MARCH 29, 2019

Data lakes are centralized repositories that can store all structured and unstructured data at any desired scale. The power of the data lake lies in the fact that it often is a cost-effective way to store data. The power of the data lake lies in the fact that it often is a cost-effective way to store data.

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Data Lake Unstructured Data Cost-Benefit Data Quality 102

Data Virtualization

APRIL 21, 2022

Reading Time: 3 minutes First we had data warehouses, then came data lakes, and now the new kid on the block is the data lakehouse. But what is a data lakehouse and why should we develop one? In a way, the name describes what.

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Data Lake Data Warehouse Data Integration Management 59

AWS Big Data

FEBRUARY 22, 2023

In this post, we show how Ruparupa implemented an incrementally updated data lake to get insights into their business using Amazon Simple Storage Service (Amazon S3), AWS Glue , Apache Hudi , and Amazon QuickSight. An AWS Glue ETL job, using the Apache Hudi connector, updates the S3 data lake hourly with incremental data.

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Data Lake Dashboards Cost-Benefit Metadata 52

CIO Business Intelligence

MAY 24, 2022

Just after launching a focused data management platform for retail customers in March, enterprise data management vendor Informatica has now released two more industry-specific versions of its Intelligent Data Management Cloud (IDMC) — one for financial services, and the other for health and life sciences.

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Finance Management Metadata Data Quality 132

AWS Big Data

DECEMBER 13, 2023

In addition to using native managed AWS services that BMS didn’t need to worry about upgrading, BMS was looking to offer an ETL service to non-technical business users that could visually compose data transformation workflows and seamlessly run them on the AWS Glue Apache Spark-based serverless data integration engine.

Metadata 86

Metadata Data Lake Visualization Data Transformation 86

Jet Global

JULY 2, 2019

To address the flood of data and the needs of enterprise businesses to store, sort, and analyze that data, a new storage solution has evolved: the data lake. What’s in a Data Lake? Data warehouses do a great job of standardizing data from disparate sources for analysis. Taking a Dip.

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Data Lake Data Warehouse Big Data Machine Learning 73

AWS Big Data

NOVEMBER 22, 2023

Apache Hudi is an open table format that brings database and data warehouse capabilities to data lakes. Apache Hudi helps data engineers manage complex challenges, such as managing continuously evolving datasets with transactions while maintaining query performance.

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Data Lake Snapshot Metadata Optimization 91

AWS Big Data

MARCH 7, 2024

Organizations often need to manage a high volume of data that is growing at an extraordinary rate. At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. We think of this concept as inside-out data movement.

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Data Lake Analytics Dashboards Metrics 111

AWS Big Data

AUGUST 16, 2023

Iceberg has become very popular for its support for ACID transactions in data lakes and features like schema and partition evolution, time travel, and rollback. Iceberg captures metadata information on the state of datasets as they evolve and change over time. For more details, refer to Creating Apache Iceberg tables.

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Data Lake Metadata Snapshot Management 77

AWS Big Data

NOVEMBER 29, 2023

We have seen a strong customer demand to expand its scope to cloud-based data lakes because data lakes are increasingly the enterprise solution for large-scale data initiatives due to their power and capabilities. Let’s say that this company is located in Europe and the data product must comply with the GDPR.

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Data Lake Management Metrics Data Warehouse 101

AWS Big Data

JANUARY 24, 2024

AWS-powered data lakes, supported by the unmatched availability of Amazon Simple Storage Service (Amazon S3), can handle the scale, agility, and flexibility required to combine different data and analytics approaches. For more information, refer to Amazon S3: Allows read and write access to objects in an S3 Bucket.

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Snapshot Data Lake Metadata Optimization 98

AWS Big Data

OCTOBER 3, 2023

In our previous post Improve operational efficiencies of Apache Iceberg tables built on Amazon S3 data lakes , we discussed how you can implement solutions to improve operational efficiencies of your Amazon Simple Storage Service (Amazon S3) data lake that is using the Apache Iceberg open table format and running on the Amazon EMR big data platform.

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Optimization Snapshot Data Lake Metadata 108

AWS Big Data

FEBRUARY 29, 2024

However, enterprise data generated from siloed sources combined with the lack of a data integration strategy creates challenges for provisioning the data for generative AI applications. As part of the transformation, the objects need to be treated to ensure data privacy (for example, PII redaction).

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Data Governance Unstructured Data Metadata Data Lake 93

In(tegrate) the Clouds

MAY 1, 2016

SnapLogic published Eight Data Management Requirements for the Enterprise Data Lake. They are: Storage and Data Formats. Metadata and Governance. The company also recently hosted a webinar on Democratizing the Data Lake with Constellation Research and published 2 whitepapers from Mark Madsen.

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Data Lake Enterprise Management Metadata 40

AWS Big Data

APRIL 6, 2023

In this post, Morningstar’s Data Lake Team Leads discuss how they utilized tag-based access control in their data lake with AWS Lake Formation and enabled similar controls in Amazon Redshift. We realized we needed a data warehouse to cater to all of these consumer requirements, so we evaluated Amazon Redshift.

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Data Warehouse Data Lake Management Data-driven 83

David Menninger's Analyst Perspectives

SEPTEMBER 28, 2021

Collibra is a data governance software company that offers tools for metadata management and data cataloging. The software enables organizations to find data quickly, identify its source and assure its integrity.

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Data Governance Metadata Software Management 346

AWS Big Data

MARCH 27, 2023

Amazon Redshift Serverless makes it simple to run and scale analytics without having to manage your data warehouse infrastructure. Tags allows you to assign metadata to your AWS resources. You can define your own key and value for your resource tag, so that you can easily manage and filter your resources.

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Data Warehouse Management Snapshot Data Lake 83

AWS Big Data

AUGUST 3, 2023

Today’s modern data lakes span multiple accounts, AWS Regions, and lines of business in organizations. It’s important that their data solution gives them the ability to share and access data securely and safely across Regions. A resource link is a Data Catalog object that is a link to a database or table.

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Data Lake Metadata Management Data Processing 84

IBM Big Data Hub

OCTOBER 16, 2023

AI governance refers to the practice of directing, managing and monitoring an organization’s AI activities. It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. It can be used with both on-premise and multi-cloud environments.

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Risk Modeling Management Metadata 75

AWS Big Data

JULY 20, 2023

The Hive metastore is a repository of metadata about the SQL tables, such as database names, table names, schema, serialization and deserialization information, data location, and partition details of each table. Apache Hive, Apache Spark, Presto, and Trino can all use a Hive Metastore to retrieve metadata to run queries.

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Data Lake Metadata Data Processing Big Data 79