CIO Business Intelligence

NOVEMBER 28, 2023

But at the other end of the attention spectrum is data management, which all too frequently is perceived as being boring, tedious, the work of clerks and admins, and ridiculously expensive. Still, to truly create lasting value with data, organizations must develop data management mastery. And what do enterprises gain from that?

Management 131

Management Data Architecture Data Lake Data Strategy 131

CDW Research Hub

JULY 22, 2019

Companies today are struggling under the weight of their legacy data warehouse. These old and inefficient systems were designed for a different era, when data was a side project and access to analytics was limited to the executive team. To do so, these companies need a modern data warehouse, such as Snowflake.

Data Warehouse 54

Data Warehouse Business Intelligence Structured Data Data Architecture 54

AWS Big Data

APRIL 3, 2024

Businesses are constantly evolving, and data leaders are challenged every day to meet new requirements. For many enterprises and large organizations, it is not feasible to have one processing engine or tool to deal with the various business requirements. Andries has over 20 years of experience in the field of data and analytics.

Data Lake 94

Data Lake Snapshot Metadata Data Architecture 94

AWS Big Data

JANUARY 24, 2023

AWS Lake Formation helps with enterprise data governance and is important for a data mesh architecture. It works with the AWS Glue Data Catalog to enforce data access and governance. He specializes in migrating enterprise data warehouses to AWS Modern Data Architecture.

Data Architecture 67

Data Architecture Metadata Data Lake Snapshot 67

AWS Big Data

JUNE 10, 2024

In this post, we delve into the key aspects of using Amazon EMR for modern data management, covering topics such as data governance, data mesh deployment, and streamlined data discovery. Organizations have multiple Hive data warehouses across EMR clusters, where the metadata gets generated.

Data Lake 83

Data Lake Metadata Data Warehouse Data Processing 83

CIO Business Intelligence

JUNE 23, 2022

These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. In recent years, the term “data lakehouse” was coined to describe this architectural pattern of tabular analytics over data in the data lake.

Data Lake 98

Data Lake Data Warehouse Machine Learning Cost-Benefit 98

Cloudera

JUNE 18, 2022

These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. In recent years, the term “data lakehouse” was coined to describe this architectural pattern of tabular analytics over data in the data lake.

Data Lake 92

Data Lake Data Warehouse Machine Learning Cost-Benefit 92

CDW Research Hub

JULY 18, 2022

While many organizations understand the business need for a data and analytics cloud platform , few can quickly modernize their legacy data warehouse due to a lack of skills, resources, and data literacy. Overall data architecture and strategy. Optimizing Snowflake functionality.

Optimization 87

Optimization Data Lake Data Warehouse Manufacturing 87

Cloudera

FEBRUARY 7, 2019

A key pillar in the transformation journey is focused on robust data operations that can help ATB deliver timely, relevant and delightful service. The company sought a data management platform that would allow its enterprise to handle greater data variety, velocity and volume in a cost-effective manner.

Big Data 66

Big Data Data Analytics Analytics Data Architecture 66

AWS Big Data

JUNE 10, 2024

Enterprises and organizations across the globe want to harness the power of data to make better decisions by putting data at the center of every decision-making process. The open table format accelerates companies’ adoption of a modern data strategy because it allows them to use various tools on top of a single copy of the data.

Data Lake 109

Data Lake Metadata Snapshot Analytics 109

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 135

Analytics Data Science Unstructured Data Data mining 135

AWS Big Data

NOVEMBER 29, 2023

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

Data Warehouse 101

Data Warehouse Data Lake Analytics Machine Learning 101

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 103

Data Lake Sales Data Warehouse Snapshot 103

CDW Research Hub

OCTOBER 12, 2021

As organizations grow and evolve, many find a need for more sophisticated analytics across an ever-increasing amount of digital and consumer data. But most legacy data architectures do not have a unified data model, and they are hard-wired toward specific BI tools that do not support self-service analytics.

Data Warehouse 52

Data Warehouse Big Data Data Architecture Cost-Benefit 52

Cloudera

DECEMBER 19, 2018

Business intelligence (BI), an umbrella term coined in 1989 by Howard Dresner, Chief Research Officer at Dresner Advisory Services, refers to the ability of end-users to access and analyze enterprise data. Big Data Technologies and Architectures. The most common big data use case is data warehouse optimization.

Data Warehouse 51

Data Warehouse Analytics Big Data Data Architecture 51

AWS Big Data

FEBRUARY 1, 2024

This stack creates the following resources and necessary permissions to integrate the services: Data stream – With Amazon Kinesis Data Streams , you can send data from your streaming source to a data stream to ingest the data into a Redshift data warehouse. version cluster. version cluster.

Data Warehouse 123

Data Warehouse Dashboards Risk Management Risk 123

AWS Big Data

FEBRUARY 16, 2024

Many customers are extending their data warehouse capabilities to their data lake with Amazon Redshift. They are looking to further enhance their security posture where they can enforce access policies on their data lakes based on Amazon Simple Storage Service (Amazon S3).

Data Lake 98

Data Lake Data Warehouse Testing Business Objectives 98

AWS Big Data

NOVEMBER 28, 2023

To run analytics on their operational data, customers often build solutions that are a combination of a database, a data warehouse, and an extract, transform, and load (ETL) pipeline. ETL is the process data engineers use to combine data from different sources.

Data Warehouse 92

Data Warehouse Data-driven Machine Learning B2B 92

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 96

Analytics Data Warehouse Dashboards Testing 96

Cloudera

JANUARY 26, 2022

According to 451 Research , 96% of enterprises are actively pursuing a hybrid IT strategy. Modern, real-time businesses require accelerated cycles of innovation that are expensive and difficult to maintain with legacy data platforms. But how did the hybrid cloud come to dominate the data sector? .

Data Processing 85

Data Processing IoT Cost-Benefit Data Warehouse 85

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 105

Data Warehouse Testing Data Quality Reporting 105

Data Virtualization

MARCH 3, 2021

To remain competitive, organizations must have a data management strategy in place to effectively ingest, store, organize, and analyze data while ensuring that it is. The post Data Management Challenges for the Modern Enterprise appeared first on Data Virtualization blog.

Enterprise 75

Enterprise Management Strategy Data Lake 75

AWS Big Data

MARCH 26, 2024

The AWS modern data architecture shows a way to build a purpose-built, secure, and scalable data platform in the cloud. Learn from this to build querying capabilities across your data lake and the data warehouse. The following screenshot shows an example C360 dashboard built on QuickSight.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

IBM Big Data Hub

SEPTEMBER 19, 2023

To pursue a data science career, you need a deep understanding and expansive knowledge of machine learning and AI. And you should have experience working with big data platforms such as Hadoop or Apache Spark. It includes a range of capabilities that enable enterprises to unlock the value of their data in new ways.

Data Science 76

Data Science Data Analytics Prescriptive Analytics Analytics 76

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 131

Analytics Data Science Statistics Unstructured Data 131

AWS Big Data

APRIL 3, 2023

Tens of thousands of customers run business-critical workloads on Amazon Redshift , AWS’s fast, petabyte-scale cloud data warehouse delivering the best price-performance. With Amazon Redshift, you can query data across your data warehouse, operational data stores, and data lake using standard SQL.

Data Warehouse 98

Data Warehouse Testing Data Lake Data-driven 98

AWS Big Data

JULY 21, 2023

This leads to having data across many instances of data warehouses and data lakes using a modern data architecture in separate AWS accounts. We recently announced the integration of Amazon Redshift data sharing with AWS Lake Formation. S3 data lake – Contains the web activity and leads datasets.

Data Lake 87

Data Lake Data Warehouse Marketing Management 87

AWS Big Data

NOVEMBER 13, 2023

KEY003 | Swami Sivasubramanian (Vice President, Data and AI at AWS) | Nov. 29 | 8:30 AM – 10:30 AM (PDT) A powerful relationship between humans, data, and AI is unfolding right before us. 11:30 AM – 12:30 PM (PDT) Ceasars Forum ANT318 | Accelerate innovation with end-to-end serverless data architecture.

Analytics 111

Analytics Data Lake Data Warehouse Data-driven 111

AWS Big Data

APRIL 20, 2023

In a modern data architecture, unified analytics enable you to access the data you need, whether it’s stored in a data lake or a data warehouse. About the Authors Aniket Jiddigoudar is a Big Data Architect on the AWS Glue team. He works with customers to help improve their big data workloads.

Visualization 79

Visualization Data Warehouse Big Data Data Lake 79

erwin

DECEMBER 12, 2019

Managing metadata should not be a sub-goal of data governance. Today, metadata is the heart of enterprise data management and governance/ intelligence efforts and should have a clear strategy – rather than just something you do. Quite simply, metadata is data about data. What Is Metadata? by up to 70 percent.

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

AWS Big Data

FEBRUARY 8, 2023

AWS Glue a serverless data integration service that makes it easy to discover, prepare, and combine data for analytics, machine learning (ML), and application development. About the Authors Siva Manickam is the Director of Enterprise Architecture, Integrations, Digital Research & Development at Vyaire Medical Inc.

Testing 72

Testing Data Integration Data Lake Enterprise 72

Peter James Thomas

AUGUST 18, 2018

That was the Science, here comes the Technology… A Brief Hydrology of Data Lakes. Even back then, these were used for activities such as Analytics , Dashboards , Statistical Modelling , Data Mining and Advanced Visualisation. Of course some architectures featured both paradigms as well. In Closing.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

Alation

JULY 30, 2021

A part of that journey often involves moving fragmented on-premises data to a cloud data warehouse. You clearly shouldn’t move everything from your on-premises data warehouses. Otherwise, you can end up with a data swamp. Put differently, you can migrate faster if you know the right data to move.

Data Warehouse 52

Data Warehouse Data Governance Machine Learning Data-driven 52

AWS Big Data

MARCH 7, 2024

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. With this massive data growth, data proliferation across your data stores, data warehouse, and data lakes can become equally challenging.

Data Lake 113

Data Lake Analytics Dashboards Metrics 113

Data Virtualization

MARCH 3, 2021

Data is the fuel of the digital economy, so data-centric organizations have a distinct advantage. To remain competitive, organizations must have a data management strategy in place to effectively ingest, store, organize, and analyze data while ensuring that it is.

Management 59

Management Enterprise Strategy Data Lake 59

Data Virtualization

MARCH 3, 2021

Data is the fuel of the digital economy, so data-centric organizations have a distinct advantage. To remain competitive, organizations must have a data management strategy in place to effectively ingest, store, organize, and analyze data while ensuring that it is.

Management 52

Management Enterprise Strategy Data Lake 52

erwin

DECEMBER 12, 2019

Managing metadata should not be a sub-goal of data governance. Today, metadata is the heart of enterprise data management and governance/ intelligence efforts and should have a clear strategy – rather than just something you do. Quite simply, metadata is data about data. What Is Metadata? by up to 70 percent.

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 52