AWS Big Data

JUNE 9, 2023

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale.

Data Lake 125

Data Lake Metadata Statistics Optimization 125

AWS Big Data

OCTOBER 9, 2023

Data lakes have been gaining popularity for storing vast amounts of data from diverse sources in a scalable and cost-effective way. As the number of data consumers grows, data lake administrators often need to implement fine-grained access controls for different user profiles.

Data Lake 129

Data Lake Testing Big Data Management 129

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 98

Data Integration Data Lake Statistics Data-driven 98

AWS Big Data

OCTOBER 1, 2024

Amazon Redshift enables you to efficiently query and retrieve structured and semi-structured data from open format files in Amazon S3 data lake without having to load the data into Amazon Redshift tables. Amazon Redshift extends SQL capabilities to your data lake, enabling you to run analytical queries.

Data Lake 105

Data Lake Statistics Broadcasting Optimization 105

AWS Big Data

JUNE 10, 2024

This amalgamation empowers vendors with authority over a diverse range of workloads by virtue of owning the data. This authority extends across realms such as business intelligence, data engineering, and machine learning thus limiting the tools and capabilities that can be used. 5 seconds $0.08 8 seconds $0.07

Data Lake 122

Data Lake Metadata Snapshot Analytics 122

AWS Big Data

SEPTEMBER 10, 2024

We often see requests from customers who have started their data journey by building data lakes on Microsoft Azure, to extend access to the data to AWS services. In such scenarios, data engineers face challenges in connecting and extracting data from storage containers on Microsoft Azure.

Data Lake 107

Data Lake Metadata Management Software 107

AWS Big Data

AUGUST 9, 2023

The combination of a data lake in a serverless paradigm brings significant cost and performance benefits. By monitoring application logs, you can gain insights into job execution, troubleshoot issues promptly to ensure the overall health and reliability of data pipelines.

Data Lake 94

Data Lake Metrics Testing Cost-Benefit 94

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? The problem is not “you.”

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

Jet Global

NOVEMBER 5, 2020

Option 3: Azure Data Lakes. This leads us to Microsoft’s apparent long-term strategy for D365 F&SCM reporting: Azure Data Lakes. Azure Data Lakes are highly complex and designed with a different fundamental purpose in mind than financial and operational reporting. Data lakes are not a mature technology.

Data Lake 98

Data Lake OLAP Data Warehouse Unstructured Data 98

Jen Stirrup

MAY 5, 2020

Organizations need to recast storing their data. It is more than just some giant USB stick in the sky that’s going to store all of the data. It has a lot of services that you can use, such as Big Data analytics. You can also use Azure Data Lake storage as well, which is optimized for high-performance analytics.

Machine Learning 89

Machine Learning Data Science Data Lake Big Data 89

DataKitchen

NOVEMBER 29, 2021

If data analytics is like a factory, the DataOps Engineer owns the assembly line used to build a data and analytic product. Most organizations run the data factory using manual labor. 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

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.

Data Lake 94

Data Lake Analytics Snapshot Data Quality 94

Corinium

JUNE 6, 2019

For instance, for a variety of reasons, in the short term, CDAOS are challenged with quantifying the benefits of analytics’ investments. Some of the work is very foundational, such as building an enterprise data lake and migrating it to the cloud, which enables other more direct value-added activities such as self-service.

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

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 96

Data Lake Metadata Data Warehouse Data Processing 96

AWS Big Data

FEBRUARY 13, 2025

Amazon SageMaker Unified Studio (preview) provides a unified experience for using data, analytics, and AI capabilities. You can use familiar AWS services for model development, generative AI, data processing, and analyticsall within a single, governed environment.

Data Analytics 72

Data Analytics Analytics Modeling Management 72

AWS Big Data

AUGUST 1, 2023

Although Jira Cloud provides reporting capability, loading this data into a data lake will facilitate enrichment with other business data, as well as support the use of business intelligence (BI) tools and artificial intelligence (AI) and machine learning (ML) applications. Shane Thompson is a Sr.

Data Lake 92

Data Lake Data Transformation Data-driven Cost-Benefit 92

CIO Business Intelligence

MARCH 9, 2022

Applying artificial intelligence (AI) to data analytics for deeper, better insights and automation is a growing enterprise IT priority. But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Big Data 119

Smart Data Collective

DECEMBER 13, 2022

However, computerization in the digital age creates massive volumes of data, which has resulted in the formation of several industries, all of which rely on data and its ever-increasing relevance. Data analytics and visualization help with many such use cases. It is the time of big data. What Is Data Analytics?

Visualization 145

Visualization Key Performance Indicator Sales Advertising 145

AWS Big Data

APRIL 24, 2023

Building a data lake on Amazon Simple Storage Service (Amazon S3) provides numerous benefits for an organization. However, many use cases, like performing change data capture (CDC) from an upstream relational database to an Amazon S3-based data lake, require handling data at a record level.

Data Lake 88

Data Lake Data Governance Machine Learning Cost-Benefit 88

CIO Business Intelligence

JUNE 29, 2022

Taking the broadest possible interpretation of data analytics , Azure offers more than a dozen services — and that’s before you include Power BI, with its AI-powered analysis and new datamart option , or governance-oriented approaches such as Microsoft Purview. Azure Data Explorer. Azure Data Lake Analytics.

Data Lake 116

Data Lake Analytics Data Warehouse Machine Learning 116

IBM Big Data Hub

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

Data Science 76

Data Science Data Analytics Prescriptive Analytics Analytics 76

CIO Business Intelligence

NOVEMBER 4, 2022

Rigid requirements to ensure the accuracy of data and veracity of scientific formulas as well as machine learning algorithms and data tools are common in modern laboratories. When Bob McCowan was promoted to CIO at Regeneron Pharmaceuticals in 2018, he had previously run the data center infrastructure for the $81.5

Data Lake 124

Data Lake IT Experimentation Data-driven 124

CIO Business Intelligence

NOVEMBER 25, 2022

Carhartt’s signature workwear is near ubiquitous, and its continuing presence on factory floors and at skate parks alike is fueled in part thanks to an ongoing digital transformation that is advancing the 133-year-old Midwest company’s operations to make the most of advanced digital technologies, including the cloud, data analytics, and AI.

Data Lake 128

Data Lake Data Warehouse Unstructured Data Data Architecture 128

AWS Big Data

APRIL 18, 2024

The Salesforce Trust Intelligence Platform (TIP) log platform team is responsible for data pipeline and data lake infrastructure, providing log ingestion, normalization, persistence, search, and detection capability to ensure Salesforce is safe from threat actors. This is the bronze layer of the TIP data lake.

Optimization 101

Optimization Data Lake Management Key Performance Indicator 101

AWS Big Data

JUNE 20, 2023

Apache Iceberg is an open table format for very large analytic datasets. It manages large collections of files as tables, and it supports modern analytical data lake operations such as record-level insert, update, delete, and time travel queries. Mikhail specializes in data analytics services.

Data Lake 83

Data Lake Data Science Recreation/Entertainment Data-driven 83

AWS Big Data

DECEMBER 4, 2024

In today’s data-driven world , organizations are constantly seeking efficient ways to process and analyze vast amounts of information across data lakes and warehouses. This post will showcase how this data can also be queried by other data teams using Amazon Athena. Verify that you have Python version 3.7

Data Lake 107

Data Lake Metadata Insurance Data-driven 107

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.

Data Lake 98

Data Lake Data Warehouse Machine Learning Data-driven 98

DataKitchen

DECEMBER 9, 2022

ChatGPT> DataOps, or data operations, is a set of practices and technologies that organizations use to improve the speed, quality, and reliability of their data analytics processes. Overall, DataOps is an essential component of modern data-driven organizations. Query> DataOps. Query> Write an essay on DataOps.

Machine Learning 130

Machine Learning Data-driven Optimization Data Analytics 130

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.

Data Lake 94

Data Lake Data Warehouse Machine Learning Data-driven 94

DataKitchen

JULY 27, 2023

Let’s go through the ten Azure data pipeline tools Azure Data Factory : This cloud-based data integration service allows you to create data-driven workflows for orchestrating and automating data movement and transformation. You can use it for big data analytics and machine learning workloads.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

CIO Business Intelligence

MARCH 2, 2023

A catalyst to make this happen will be the ongoing improvements in AI-enabled data capture. Fast and accurate data extraction will speed up transactions and automation capabilities, and be the foundational technology within any business intelligence or data analytics platform, enabling better collaboration and B2B communications, he says.

Data Lake 143

Data Lake Forecasting B2B Optimization 143

Jedox

OCTOBER 22, 2020

The term “data analytics” refers to the process of examining datasets to draw conclusions about the information they contain. Data analysis techniques enhance the ability to take raw data and uncover patterns to extract valuable insights from it. Data analytics is not new.

Data Analytics 69

Data Analytics Analytics Unstructured Data Data mining 69

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. This zero-ETL integration reduces the complexity and operational burden of data replication to let you focus on deriving insights from your data.

Analytics 59

Analytics Data Lake Metadata Data Warehouse 59

Cloudera

MAY 30, 2024

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission-critical, large-scale data analytics and AI use cases—including enterprise data warehouses. Support for Modern Analytics Workloads : With support for both SQL-based querying and advanced analytics frameworks (e.g.,

Data Lake 74

Data Lake Analytics Data Warehouse Machine Learning 74

AWS Big Data

MARCH 27, 2024

Amazon Redshift integrates with AWS HealthLake and data lakes through Redshift Spectrum and Amazon S3 auto-copy features, enabling you to query data directly from files on Amazon S3. This means you no longer have to create an external schema in Amazon Redshift to use the data lake tables cataloged in the Data Catalog.

Data Analytics 106

Data Analytics Analytics Data Warehouse Data Lake 106

AWS Big Data

DECEMBER 18, 2023

Customers use Amazon Redshift as a key component of their data architecture to drive use cases from typical dashboarding to self-service analytics, real-time analytics, machine learning (ML), data sharing and monetization, and more.

Data Warehouse 109

Data Warehouse Machine Learning Data-driven Data Lake 109

CIO Business Intelligence

APRIL 26, 2024

billion acquisition of data and analytics company Neustar in 2021, TransUnion has expanded into other services such as marketing, fraud detection and prevention, and robust analytical services. We’re modernizing existing products to get to this entire data analytics value chain.” But following its $3.1

Modeling 114

Modeling IT Machine Learning Data Governance 114