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. This is critical for fast-moving enterprises to augment data structures to support new use cases. This hampers agility and time to insight.

Snapshot 111

Snapshot Data Lake Metadata Recreation/Entertainment 111

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.

Data Lake 86

Data Lake Metadata Cost-Benefit Management 86

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.

Data Lake 102

Data Lake Unstructured Data Cost-Benefit Data Quality 102

Timo Elliott

NOVEMBER 21, 2022

Last week I was in beautiful Sydney, Australia for the Gartner Data and Analytics Conference. Here’s a quick video summary: One of the big things that struck me was the changing role of data. Data is useless. It’s possible, but it takes huge amounts of time and effort.

Data Analytics 98

Data Analytics Analytics Recreation/Entertainment Data Lake 98

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.

Data Lake 59

Data Lake Data Warehouse Data Integration Management 59

Ontotext

APRIL 10, 2024

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. Teams can’t access data to build their business use cases. For example, a product data tag is basic metadata.

Metadata 52

Metadata Data Lake Data Warehouse Data Quality 52

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.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

AWS Big Data

DECEMBER 13, 2023

For the past 5 years, BMS has used a custom framework called Enterprise Data Lake Services (EDLS) to create ETL jobs for business users. EDLS job steps and metadata Every EDLS job comprises one or more job steps chained together and run in a predefined order orchestrated by the custom ETL framework.

Metadata 87

Metadata Data Lake Visualization Data Transformation 87

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.

Data Lake 75

Data Lake Metadata Snapshot Management 75

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. It will never remove files that are still required by a non-expired snapshot.

Snapshot 100

Snapshot Data Lake Metadata Optimization 100

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.”.

Metadata 52

Metadata Management Data Lake Data Governance 52

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.

Optimization 109

Optimization Snapshot Data Lake Metadata 109

AWS Big Data

MARCH 7, 2023

This post provides guidance on how to build scalable analytical solutions for gaming industry use cases using Amazon Redshift Serverless. Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. Data hubs and data lakes can coexist in an organization, complementing each other.

Analytics 69

Analytics Data Warehouse Data Lake Metadata 69

AWS Big Data

FEBRUARY 29, 2024

To provide a response that includes the enterprise context, each user prompt needs to be augmented with a combination of insights from structured data from the data warehouse and unstructured data from the enterprise data lake.

Data Governance 95

Data Governance Unstructured Data Metadata Data Lake 95

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.

Data Lake 83

Data Lake Metadata Management Data Processing 83

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.

Data Lake 77

Data Lake Metadata Data Processing Big Data 77

Ontotext

MAY 2, 2024

Data leaders today are faced with an almost impossible challenge. Particularly those on the “the create side of the house” who are tasked to deliver insights and analytics. Such inconsistencies bring lowered trust in the outcomes analytics and insights leaders try to get.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes. Iterations of the lakehouse.

Data Lake 90

Data Lake Data Warehouse Machine Learning Cost-Benefit 90

AWS Big Data

JANUARY 17, 2024

With Amazon EMR 6.15, we launched AWS Lake Formation based fine-grained access controls (FGAC) on Open Table Formats (OTFs), including Apache Hudi, Apache Iceberg, and Delta lake. Many large enterprise companies seek to use their transactional data lake to gain insights and improve decision-making.

Data Lake 92

Data Lake Snapshot Big Data Data-driven 92

Andrew White

DECEMBER 9, 2019

The client had recently engaged with a well-known consulting company that had recommended a large data catalog effort to collect all enterprise metadata to help identify all data and business issues. Modern data (and analytics) governance does not necessarily need: Wall-to-wall discovery of your data and metadata.

Analytics 66

Analytics Data Lake Data Governance Metadata 66

AWS Big Data

JUNE 6, 2023

As most organizations, that have turned to Google Analytics (GA) as a digital analytics solution, mature they discover a more pressing need to integrate this data silo with the rest of their organization’s data to enable better analytics and resulting product development and fraud detection.

Analytics 56

Analytics Data Lake Testing Optimization 56

AWS Big Data

DECEMBER 5, 2023

This cut down significantly on analytical turnaround times. The CARTO Analytics Toolbox for Redshift is composed of a set of user-defined functions and procedures organized in a set of modules based on the functionality they offer. These table definitions are used as the metadata repository for external tables in Amazon Redshift.

Measurement 80

Measurement Dashboards Data Warehouse Analytics 80

DataKitchen

AUGUST 3, 2021

First-generation – expensive, proprietary enterprise data warehouse and business intelligence platforms maintained by a specialized team drowning in technical debt. Second-generation – gigantic, complex data lake maintained by a specialized team drowning in technical debt. See the pattern?

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

CIO Business Intelligence

JUNE 23, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes. Iterations of the lakehouse.

Data Lake 82

Data Lake Data Warehouse Machine Learning Cost-Benefit 82

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.

Data Governance 349

Data Governance Metadata Software Management 349

AWS Big Data

JANUARY 8, 2024

This is the first post to a blog series that offers common architectural patterns in building real-time data streaming infrastructures using Kinesis Data Streams for a wide range of use cases. In this post, we will review the common architectural patterns of two use cases: Time Series Data Analysis and Event Driven Microservices.

Analytics 111

Analytics IoT Data-driven Snapshot 111

CIO Business Intelligence

MAY 24, 2022

Some of the accelerators included as part of the new platform are integrations with Salesforce, NPI data, National Patient Account Services, Workday, Oracle Fusion HCM Cloud, Orange HRM, Salesforce Health Cloud, MedPro, healthcare-focused cloud company Veeva, and HR vendor UltiPro. Analytics for faster decision making.

Finance 130

Finance Management Metadata Data Quality 130

AWS Big Data

APRIL 19, 2023

We split the solution into two primary components: generating Spark job metadata and running the SQL on Amazon EMR. The first component (metadata setup) consumes existing Hive job configurations and generates metadata such as number of parameters, number of actions (steps), and file formats. sql_path SQL file name.

Metadata 77

Metadata Testing Data Lake Consulting 77

Cloudera

JUNE 25, 2021

Many Cloudera customers are making the transition from being completely on-prem to cloud by either backing up their data in the cloud, or running multi-functional analytics on CDP Public cloud in AWS or Azure. The Replication Manager service facilitates both disaster recovery and data migration across different environments.

Data Lake 69

Data Lake Metadata Unstructured Data Management 69

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 79

Data Lake Data Governance Data Architecture Data Warehouse 79

CIO Business Intelligence

OCTOBER 13, 2023

Solutions data architect: These individuals design and implement data solutions for specific business needs, including data warehouses, data marts, and data lakes. Application data architect: The application data architect designs and implements data models for specific software applications.

Data Architecture 126

Data Architecture Data Warehouse Statistics Visualization 126

DataKitchen

AUGUST 9, 2021

The domain also includes code that acts upon the data, including tools, pipelines, and other artifacts that drive analytics execution. The domain requires a team that creates/updates/runs the domain, and we can’t forget metadata: catalogs, lineage, test results, processing history, etc., ….

Testing 246

Testing Data Lake Metadata Publishing 246

Cloudera

MARCH 17, 2023

The one key component that is missing is a common, shared table format, that can be used by all analytic services accessing the lakehouse data. The table format provides the necessary structure for the unstructured data that is missing in a data lake, using a schema or metadata definition, to bring it closer to a data warehouse.

Unstructured Data 61

Unstructured Data Data Lake Data Warehouse Machine Learning 61

AWS Big Data

SEPTEMBER 13, 2023

The Analytics specialty practice of AWS Professional Services (AWS ProServe) helps customers across the globe with modern data architecture implementations on the AWS Cloud. Of those tables, some are larger (such as in terms of record volume) than others, and some are updated more frequently than others.

Data Lake 90

Data Lake Data Processing Metadata Snapshot 90

AWS Big Data

MARCH 25, 2024

Streaming jobs constantly ingest new data to synchronize across systems and can perform enrichment, transformations, joins, and aggregations across windows of time more efficiently. OpenSearch Service provides support for native ingestion from Kinesis data streams or MSK topics.

Data Lake 90

Data Lake Unstructured Data Management Modeling 90

Alation

FEBRUARY 13, 2020

Why do we need a data catalog? What does a data catalog do? These are all good questions and a logical place to start your data cataloging journey. Data catalogs have become the standard for metadata management in the age of big data and self-service analytics. What is a Data Catalog?

Metadata 64

Metadata Data Lake Recreation/Entertainment Big Data 64

Cloudera

JUNE 7, 2023

It operates independently from compute and storage layers, offering integrated security and governance based on metadata. With persistent context across analytics and cloud environments, SDX simplifies data delivery and access with a unified multi-tenant model. Understanding your data is critical to protecting the data.

Metadata 79

Metadata Data Lake Optimization Modeling 79