CDW Research Hub

OCTOBER 25, 2019

As we review data transformation and modernization strategies with our clients, we find many are investigating Snowflake as a data warehouse solution due to its ease of use, speed, and increased flexibility over a traditional data warehouse offering.

Data Warehouse 40

Data Warehouse Testing Strategy Data-driven 40

Sisense

MARCH 14, 2021

However, when investigating big data from the perspective of computer science research, we happily discover much clearer use of this cluster of confusing concepts. As we move from right to left in the diagram, from big data to BI, we notice that unstructured data transforms into structured data.

Big Data 52

Big Data IoT Data Warehouse Data-driven 52

AWS Big Data

JULY 31, 2023

This solution decouples the ETL and analytics workloads from our transactional data source Amazon Aurora, and uses Amazon Redshift as the data warehouse solution to build a data mart. We use Amazon Redshift as the data warehouse to implement the data mart solution. Deepti Venuturumilli is a Sr.

Sales 52

Sales Data Warehouse Visualization Testing 52

AWS Big Data

JULY 25, 2023

Today, in order to accelerate and scale data analytics, companies are looking for an approach to minimize infrastructure management and predict computing needs for different types of workloads, including spikes and ad hoc analytics. Prerequisites To complete the integration, you need a Redshift Serverless data warehouse.

Data Analytics 52

Data Analytics Data Warehouse Analytics Data Processing 52

CIO Business Intelligence

JUNE 29, 2022

Insights hidden in your data are essential for optimizing business operations, finetuning your customer experience, and developing new products — or new lines of business, like predictive maintenance. And as businesses contend with increasingly large amounts of data, the cloud is fast becoming the logical place where analytics work gets done.

Data Lake 116

Data Lake Analytics Data Warehouse Machine Learning 116

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 88

Data Warehouse Data Lake Analytics Data Science 88

CIO Business Intelligence

DECEMBER 22, 2022

DataOps (data operations) is an agile, process-oriented methodology for developing and delivering analytics. It brings together DevOps teams with data engineers and data scientists to provide the tools, processes, and organizational structures to support the data-focused enterprise. What is DataOps?

Analytics 130

Analytics Machine Learning Software Data Quality 130

AWS Big Data

OCTOBER 27, 2023

Data integration is the foundation of robust data analytics. It encompasses the discovery, preparation, and composition of data from diverse sources. In the modern data landscape, accessing, integrating, and transforming data from diverse sources is a vital process for data-driven decision-making.

Analytics 93

Analytics Visualization Data Integration Cost-Benefit 93

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

AWS Big Data

APRIL 30, 2024

Amazon Q Developer can now generate complex data integration jobs with multiple sources, destinations, and data transformations. Generated jobs can use a variety of data transformations, including filter, project, union, join, and custom user-supplied SQL. In his spare time, he enjoys cycling with his road bike.

Data Integration 100

Data Integration Data Lake Data Warehouse Software 100

Alation

OCTOBER 27, 2022

Few actors in the modern data stack have inspired the enthusiasm and fervent support as dbt. This data transformation tool enables data analysts and engineers to transform, test and document data in the cloud data warehouse. Bindu Chandramohan, Lead, Data Analytics, Alation : Thanks, Jason!

Metrics 52

Metrics Dashboards Sales Reporting 52

IBM Big Data Hub

MARCH 14, 2024

The solution: IBM databases on AWS To solve for these challenges, IBM’s portfolio of SaaS database solutions on Amazon Web Services (AWS), enables enterprises to scale applications, analytics and AI across the hybrid cloud landscape. It enables secure data sharing for analytics and AI across your ecosystem.

Cost-Benefit 84

Cost-Benefit Metadata Optimization Management 84

Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. These two functions are nearly inseparable as we move further into a world of analytics that blends sources of varying volume, variety, veracity, and velocity. But this was only the tip of the analytics iceberg.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

AWS Big Data

OCTOBER 18, 2023

Apache Hive is a distributed, fault-tolerant data warehouse system that enables analytics at a massive scale. Spark SQL is an Apache Spark module for structured data processing. The support to run Spark SQL through the StartJobRun API in EMR on EKS has further enabled FINRA’s innovation in data analytics.

Big Data 77

Big Data Data Processing Interactive Testing 77

AWS Big Data

MARCH 3, 2023

In this post, we share how the AWS Data Lab helped Tricentis to improve their software as a service (SaaS) Tricentis Analytics platform with insights powered by Amazon Redshift. While aggregating, summarizing, and aligning to a common information model, all transformations must not affect the integrity of data from its source.

Software 52

Software Data Lake Testing Cost-Benefit 52

AWS Big Data

MARCH 3, 2023

You can then apply transformations and store data in Delta format for managing inserts, updates, and deletes. Amazon EMR Serverless is a serverless option in Amazon EMR that makes it easy for data analysts and engineers to run open-source big data analytics frameworks without configuring, managing, and scaling clusters or servers.

Data Lake 79

Data Lake Dashboards Metrics Metadata 79

CDW Research Hub

JULY 23, 2021

Get hands-on experience with the data cloud. Gain experience and understanding of how to drive better business decisions with your data. Our fifth video will demonstrate data transformation and orchestration with Matillion into Snowflake. Learn about current trends.

Structured Data 52

Structured Data Consulting Strategy Data Strategy 52

Smart Data Collective

OCTOBER 13, 2021

There are countless examples of big data transforming many different industries. There is no disputing the fact that the collection and analysis of massive amounts of unstructured data has been a huge breakthrough. If we talk about Big Data, data visualization is crucial to more successfully drive high-level decision making.

Visualization 135

Visualization Cost-Benefit Big Data Prescriptive Analytics 135

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 98

Analytics Data Lake Metadata Cost-Benefit 98

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. On the AWS CloudFormation console, return to the stack.

Data Lake 81

Data Lake Data Transformation Cost-Benefit Data-driven 81

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 86

Data Lake Data Warehouse Data-driven B2B 86

IBM Big Data Hub

JUNE 15, 2023

The proliferation of data silos also inhibits the unification and enrichment of data which is essential to unlocking the new insights. Moreover, increased regulatory requirements make it harder for enterprises to democratize data access and scale the adoption of analytics and artificial intelligence (AI).

Data Warehouse 98

Data Warehouse Data Lake Optimization Data-driven 98

Ontotext

FEBRUARY 12, 2024

Transferring ownership of data/datasets to domain-specific units that possess a deeper understanding of rules around the data empowers teams, improves data quality and trust, and greatly accelerates the building of data models and analytics.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

Jet Global

MAY 1, 2023

Introduction Why should I read the definitive guide to embedded analytics? But many companies fail to achieve this goal because they struggle to provide the reporting and analytics users have come to expect. The Definitive Guide to Embedded Analytics is designed to answer any and all questions you have about the topic.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

Jet Global

MAY 9, 2024

A data pipeline is a series of processes that move raw data from one or more sources to one or more destinations, often transforming and processing the data along the way. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

Jet Global

APRIL 24, 2024

In the rapidly-evolving world of embedded analytics and business intelligence, one important question has emerged at the forefront: How can you leverage artificial intelligence (AI) to enhance your data analysis? How does AI impact analytics and how do you get started? Forget the one-size-fits-all approach.

Business Intelligence 52

Business Intelligence Dashboards Software Reporting 52