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 84

Data Science Data Analytics Prescriptive Analytics Analytics 84

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

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 112

Data Lake Analytics Dashboards Metrics 112

AWS Big Data

APRIL 3, 2024

They understand that a one-size-fits-all approach no longer works, and recognize the value in adopting scalable, flexible tools and open data formats to support interoperability in a modern data architecture to accelerate the delivery of new solutions. Andries has over 20 years of experience in the field of data and analytics.

Data Lake 94

Data Lake Snapshot Metadata Data Architecture 94

CIO Business Intelligence

AUGUST 9, 2022

What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines used by data scientists, data-centric applications, and other data consumers. Data engineer job description.

Analytics 121

Analytics Data Science Statistics Unstructured Data 121

Cloudera

DECEMBER 19, 2018

Data analytics priorities have shifted this year. Don’t blink or you might miss what leading organizations are doing to modernize their analytic and data warehousing environments. Natural language analytics and streaming data analytics are emerging technologies that will impact the market.

Data Warehouse 52

Data Warehouse Analytics Big Data Data Architecture 52

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. All these architecture patterns are integrated with Amazon Kinesis Data Streams.

Analytics 111

Analytics IoT Data-driven Snapshot 111

Cloudera

FEBRUARY 7, 2019

Who knew that in that search, the company would become the first organization to globally run SAS Viya, a cloud-optimized software, with HDP on GCP to enable modern analytics use cases powered by SAS analytics tools. Implementing a Modern Data Architecture. Reducing Analytic Time to Value by More Than 90 Percent.

Big Data 64

Big Data Data Analytics Analytics Data Architecture 64

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

CIO Business Intelligence

NOVEMBER 28, 2023

Still, to truly create lasting value with data, organizations must develop data management mastery. This means excelling in the under-the-radar disciplines of data architecture and data governance. The knock-on impact of this lack of analyst coverage is a paucity of data about monies being spent on data management.

Management 108

Management Data Architecture Data Lake Data Strategy 108

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. Sirius has created a lightweight development tool to rapidly build and deploy best-practice data models.

Optimization 87

Optimization Data Lake Data Warehouse Manufacturing 87

AWS Big Data

NOVEMBER 28, 2023

As customers become more data driven and use data as a source of competitive advantage, they want to easily run analytics on their data to better understand their core business drivers to grow sales, reduce costs, and optimize their businesses.

Data Warehouse 92

Data Warehouse Data-driven Machine Learning B2B 92

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 102

Data Lake Sales Data Warehouse Snapshot 102

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.

Data Warehouse 122

Data Warehouse Dashboards Risk Management Risk 122

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

AWS Big Data

MAY 17, 2023

Credit: Phil Goldstein Jerry Wang, Peloton’s Director of Data Engineering (left), and Evy Kho, Peloton’s Manager of Subscription Analytics, discuss how the company has benefited from using Amazon Redshift. One group performed extract, transform, and load (ETL) operations to take raw data and make it available for analysis.

Data Warehouse 111

Data Warehouse Cost-Benefit Sales Data-driven 111

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 97

Data Lake Data Warehouse Testing Business Objectives 97

AWS Big Data

JANUARY 31, 2023

In this post, we are excited to summarize the features that the AWS Glue Data Catalog, AWS Glue crawler, and Lake Formation teams delivered in 2022. Whether you are a data platform builder, data engineer, data scientist, or any technology leader interested in data lake solutions, this post is for you.

Data Lake 79

Data Lake Data Governance Data Architecture Data Warehouse 79

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. Third-party APIs – These provide analytics and survey data related to ecommerce websites.

Data Warehouse 104

Data Warehouse Testing Data Quality Reporting 104

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 97

Data Warehouse Testing Data Lake Data-driven 97

Cloudera

JANUARY 26, 2022

Modern, real-time businesses require accelerated cycles of innovation that are expensive and difficult to maintain with legacy data platforms. The hybrid cloud’s premise—two data architectures fused together—gives companies options to leverage those solutions and to address decision-making criteria, on a case-by-case basis. .

Data Processing 83

Data Processing IoT Cost-Benefit Digital Transformation 83

AWS Big Data

JUNE 6, 2023

Deenbandhu Prasad is a Senior Analytics Specialist at AWS, specializing in big data services. He is passionate about helping customers build modern data architecture on the AWS Cloud. He has helped customers of all sizes implement data management, data warehouse, and data lake solutions.

Data Quality 69

Data Quality Metrics Visualization Dashboards 69

Peter James Thomas

AUGUST 18, 2018

From 2000 to 2015, I had some success [5] with designing and implementing Data Warehouse architectures much like the following: As a lot of my work then was in Insurance or related fields, the Analytical Repositories tended to be Actuarial Databases and / or Exposure Management Databases, developed in collaboration with such teams.

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

APRIL 19, 2023

With the right analytics approach, this is possible. In this post, we look at three key challenges that customers face with growing data and how a modern data warehouse and analytics system like Amazon Redshift can meet these challenges across industries and segments.

Data Warehouse 56

Data Warehouse Data Lake Unstructured Data Optimization 56

IBM Big Data Hub

JULY 5, 2022

In today’s world of complex data architectures and emerging technologies, databases can sometimes be undervalued and unrecognized. When we look ahead, that same architectural foundation we have spent decades perfecting and innovating is also bringing Db2 into future. Nedbank builds a scalable data warehouse architecture .

Data Lake 96

Data Lake Data Warehouse Publishing Structured Data 96

AWS Big Data

FEBRUARY 8, 2023

Solution overview Vyaire’s iDataHub powered by AWS Glue has been effectively used for data movement between SAP ERP and ServiceMax. 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.

Testing 73

Testing Data Integration Data Lake Enterprise 73

AWS Big Data

MARCH 25, 2024

To understand the best ways to make API calls via Apache Flink, refer to Common streaming data enrichment patterns in Amazon Kinesis Data Analytics for Apache Flink. OpenSearch Service provides support for native ingestion from Kinesis data streams or MSK topics.

Data Lake 90

Data Lake Unstructured Data Management Modeling 90

AWS Big Data

MAY 18, 2023

It’s even harder when your organization is dealing with silos that impede data access across different data stores. Seamless data integration is a key requirement in a modern data architecture to break down data silos. About the authors Gonzalo Herreros is a Senior Big Data Architect on the AWS Glue team.

Testing 75

Testing Data Lake Cost-Benefit Data Integration 75

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 95

Analytics Data Warehouse Testing Dashboards 95

erwin

DECEMBER 12, 2019

The Role of Metadata in Data Governance. As data continues to proliferate, so does the need for data and analytics initiatives to make sense of it all. Quicker Project Delivery: Accelerate Big Data deployments, Data Vaults, data warehouse modernization, cloud migration, etc.,

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

Data Virtualization

SEPTEMBER 16, 2020

Organizations are leveraging cloud analytics to extract useful insights from big data, which draws from a variety of sources such as mobile phones, Internet of. Organizations all over the world are migrating their IT infrastructures and applications to the cloud.

Big Data 59

Big Data Internet of Things Analytics IT 59

AWS Big Data

FEBRUARY 9, 2023

To achieve this, they combine their CRM data with a wealth of information already available in their data warehouse, enterprise systems, or other software as a service (SaaS) applications. One widely used approach is getting the CRM data into your data warehouse and keeping it up to date through frequent data synchronization.

Data Warehouse 74

Data Warehouse Data-driven Snapshot Testing 74

Data Virtualization

DECEMBER 15, 2022

Reading Time: 3 minutes One of the biggest challenges for organizations is to integrate data from various sources. Despite modern advancements such as big data technologies and cloud, data often ends up in organized silos, but this means that cloud data is separated from.

Big Data 52

Big Data Data Integration Technology Management 52

BizAcuity

APRIL 14, 2022

Big Data technology in today’s world. Did you know that the big data and business analytics market is valued at $198.08 Or that the US economy loses up to $3 trillion per year due to poor data quality? quintillion bytes of data which means an average person generates over 1.5 Big Data Ecosystem.

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

erwin

DECEMBER 12, 2019

The Role of Metadata in Data Governance. As data continues to proliferate, so does the need for data and analytics initiatives to make sense of it all. Quicker Project Delivery: Accelerate Big Data deployments, Data Vaults, data warehouse modernization, cloud migration, etc.,

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 52

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