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

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 93

Data Lake Data Warehouse Machine Learning Cost-Benefit 93

AWS Big Data

DECEMBER 21, 2023

To speed up the self-service analytics and foster innovation based on data, a solution was needed to provide ways to allow any team to create data products on their own in a decentralized manner. To create and manage the data products, smava uses Amazon Redshift , a cloud data warehouse.

Data Lake 87

Data Lake Data Warehouse Data-driven B2B 87

CIO Business Intelligence

APRIL 5, 2022

Investment in data warehouses is rapidly rising, projected to reach $51.18 billion by 2028 as the technology becomes a vital cog for enterprises seeking to be more data-driven by using advanced analytics. Data warehouses are, of course, no new concept. More data, more demanding. “As

Data Warehouse 96

Data Warehouse Visualization Data-driven Data Architecture 96

Smarten

MAY 30, 2023

When a business plans to launch an augmented analytics or business intelligence solution, it must carefully plan for user adoption – especially if the launch of this solution is part of a larger strategy for self-serve business user analytics and the Citizen Data Scientist approach to data use across the enterprise.

Slice and Dice 52

Slice and Dice Business Intelligence Cost-Benefit Dashboards 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.

Data Lake 89

Data Lake Data Warehouse Machine Learning Cost-Benefit 89

AWS Big Data

FEBRUARY 1, 2024

In this post, we provide a solution architecture that describes how you can process data from three different types of sources—streaming, transactional, and third-party reference data—and aggregate them in Amazon Redshift for business intelligence (BI) reporting. version cluster. version cluster.

Data Warehouse 121

Data Warehouse Dashboards Risk Management Risk 121

CIO Business Intelligence

SEPTEMBER 14, 2023

Database-centric: In larger organizations, where managing the flow of data is a full-time job, data engineers focus on analytics databases. Database-centric data engineers work with data warehouses across multiple databases and are responsible for developing table schemas.

Analytics 133

Analytics Data Science Unstructured Data Data mining 133

AWS Big Data

NOVEMBER 13, 2023

Amazon Redshift is a fully managed data warehousing service that offers both provisioned and serverless options, making it more efficient to run and scale analytics without having to manage your data warehouse. These upstream data sources constitute the data producer components.

Data Warehouse 90

Data Warehouse Data Lake Analytics Data Science 90

CDW Research Hub

JULY 27, 2021

Data volumes are growing exponentially, and traditional, on-premises data warehouses are constrained, overly complex, and costly to scale. Companies feel locked into these systems as they are often tied to business-critical operations. Reduce the total cost of ownership of the data infrastructure.

Data Warehouse 52

Data Warehouse Data Lake Data Architecture Consulting 52

Cloudera

DECEMBER 19, 2018

Data analytics priorities have shifted this year. Growth factors and business priority are ever changing. Don’t blink or you might miss what leading organizations are doing to modernize their analytic and data warehousing environments. The most common big data use case is data warehouse optimization.

Data Warehouse 52

Data Warehouse Analytics Big Data Data Architecture 52

AWS Big Data

OCTOBER 18, 2023

Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse that provides the flexibility to use provisioned or serverless compute for your analytical workloads. The decoupled compute and storage architecture of Amazon Redshift enables you to build highly scalable, resilient, and cost-effective workloads.

Analytics 94

Analytics Data Warehouse Testing Dashboards 94

AWS Big Data

NOVEMBER 9, 2023

It allows users to write data transformation code, run it, and test the output, all within the framework it provides. Use case The Enterprise Data Analytics group of a large jewelry retailer embarked on their cloud journey with AWS in 2021. It’s raw, unprocessed data straight from the source.

Data Warehouse 103

Data Warehouse Testing Data Quality Reporting 103

CIO Business Intelligence

JUNE 23, 2023

There are also no-code data engineering and AI/ML platforms so regular business users, as well as data engineers, scientists and DevOps staff, can rapidly develop, deploy, and derive business value.

Data Strategy 109

Data Strategy Strategy Visualization Consulting 109

CIO Business Intelligence

AUGUST 9, 2022

Database-centric: In larger organizations, where managing the flow of data is a full-time job, data engineers focus on analytics databases. Database-centric data engineers work with data warehouses across multiple databases and are responsible for developing table schemas. Data engineer job description.

Analytics 126

Analytics Data Science Statistics Unstructured Data 126

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 124

Data Lake Data Warehouse Unstructured Data Data Architecture 124

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 111

Data Lake Metadata Optimization Statistics 111

BizAcuity

APRIL 14, 2022

Its effective data analytics that allows personalization in marketing & sales, identifying new opportunities, making important decisions and being sustainable for the long term. Competitive Advantages to using Big Data Analytics. Challenges associated with Data Management and Optimizing Big Data.

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

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 108

Data Lake Unstructured Data Data Warehouse Data Quality 108

Alation

APRIL 14, 2022

Data discovery is also critical for data governance , which, when ineffective, can actually hinder organizational growth. And, as organizations progress and grow, “data drift” starts to impact data usage, models, and your business. On-premises business intelligence and databases. Scheduling.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

O'Reilly on Data

SEPTEMBER 11, 2019

Terms that relate to data engineering, data management, and data analytics dominate the top tiers of proposal topics. This is noteworthy for several reasons: first, the top three terms in our data set relate in one way or another to ML. New trends in data architecture and data services.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

IBM Big Data Hub

AUGUST 4, 2023

Today, the way businesses use data is much more fluid; data literate employees use data across hundreds of apps, analyze data for better decision-making, and access data from numerous locations. This includes tools that do not require advanced technical skill or deep understanding of data analytics to use.

Data Architecture 64

Data Architecture Data Lake Machine Learning Data Governance 64

CIO Business Intelligence

AUGUST 3, 2023

When global technology company Lenovo started utilizing data analytics, they helped identify a new market niche for its gaming laptops, and powered remote diagnostics so their customers got the most from their servers and other devices. Each of the acquired companies had multiple data sets with different primary keys, says Hepworth. “We

Analytics 97

Analytics Data Lake Metadata Cost-Benefit 97

Jet Global

MAY 1, 2023

We hope this guide will transform how you build value for your products with embedded analytics. Learn how embedded analytics are different from traditional business intelligence and what analytics users expect. that gathers data from many sources. CRM, ERP, EHR/EMR) or portals (e.g., It’s all about context.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52