AWS Big Data

NOVEMBER 7, 2023

Second, organizations still need transformations like cleansing, deduplication, and combining datasets for analysis and machine learning (ML). For these, AWS Glue provides fast, scalable data transformation. Prior to his current role, he was VP of Analytics at AWS, where he worked across the entire AWS database portfolio.

Dashboards 73

Dashboards Data-driven Data Integration Data Lake 73

AWS Big Data

APRIL 11, 2023

By collecting data from store sensors using AWS IoT Core , ingesting it using AWS Lambda to Amazon Aurora Serverless , and transforming it using AWS Glue from a database to an Amazon Simple Storage Service (Amazon S3) data lake, retailers can gain deep insights into their inventory and customer behavior.

Forecasting 73

Forecasting Management IoT Data-driven 73

AWS Big Data

NOVEMBER 9, 2023

In this post, we delve into a case study for a retail use case, exploring how the Data Build Tool (dbt) was used effectively within an AWS environment to build a high-performing, efficient, and modern data platform. It does this by helping teams handle the T in ETL (extract, transform, and load) processes.

Data Warehouse 101

Data Warehouse Testing Data Quality Reporting 101

AWS Big Data

DECEMBER 5, 2023

For files with known structures, a Redshift stored procedure is used, which takes the file location and table name as parameters and runs a COPY command to load the raw data into corresponding Redshift tables. He has worked on building and tuning data warehouse and data lake solutions for over 15 years.

Measurement 80

Measurement Dashboards Data Warehouse Analytics 80

AWS Big Data

MARCH 3, 2023

From detailed design to a beta release, Tricentis had customers expecting to consume data from a data lake specific to only their data, and all of the data that had been generated for over a decade. Data export As stated earlier, some customers want to get an export of their test data and create their data lake.

Software 52

Software Data Lake Testing Cost-Benefit 52

IBM Big Data Hub

OCTOBER 16, 2023

How to scale AL and ML with built-in governance A fit-for-purpose data store built on an open lakehouse architecture allows you to scale AI and ML while providing built-in governance tools. A data store lets a business connect existing data with new data and discover new insights with real-time analytics and business intelligence.

Risk 74

Risk Modeling Management Metadata 74

CIO Business Intelligence

OCTOBER 18, 2022

Resultant recommended a new, on-prem data infrastructure, complete with data lakes to provide stake holders with a better way to manage data reliability, accuracy, and timeliness. The process included co-developing a comprehensive roadmap, project plan, and budget with the business operations team.

Data Transformation 141

Data Transformation Consulting Data Lake Reporting 141

AWS Big Data

APRIL 5, 2023

The company decided to use AWS to unify its business intelligence (BI) and reporting strategy for both internal organization-wide use cases and in-product embedded analytics targeted at its customers. The company also used the opportunity to reimagine its data pipeline and architecture.

Dashboards 52

Dashboards Reporting Cost-Benefit Visualization 52

CIO Business Intelligence

JUNE 29, 2022

If you’re used to using SQL Server Analysis Services for business intelligence, Analysis Services offers that enterprise-grade analytics engine as a cloud service that you can also connect to Power BI. Azure Data Factory. Azure Data Lake Analytics. Microsoft. Azure Analysis Services.

Data Lake 114

Data Lake Analytics Data Warehouse Machine Learning 114

AWS Big Data

FEBRUARY 8, 2023

Amazon Redshift enables you to run complex SQL analytics at scale and performance on terabytes to petabytes of structured and unstructured data, and make the insights widely available through popular business intelligence (BI) and analytics tools.

Data Quality 74

Data Quality Testing Data Warehouse Unstructured Data 74

IBM Big Data Hub

JANUARY 18, 2023

Data platform architecture has an interesting history. Towards the turn of millennium, enterprises started to realize that the reporting and business intelligence workload required a new solution rather than the transactional applications. A read-optimized platform that can integrate data from multiple applications emerged.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

Cloudera

JUNE 30, 2022

These tools empower analysts and data scientists to easily collaborate on the same data, with their choice of tools and analytic engines. No more lock-in, unnecessary data transformations, or data movement across tools and clouds just to extract insights out of the data.

Data Lake 87

Data Lake Data Architecture Metadata Data Warehouse 87

IBM Big Data Hub

MARCH 14, 2024

.   Request a live demo or start a proof of concept with Amazon RDS for Db2 Db2 Warehouse SaaS on AWS The cloud-native Db2 Warehouse fulfills your price and performance objectives for mission-critical operational analytics, business intelligence (BI) and mixed workloads.

Cost-Benefit 80

Cost-Benefit Metadata Optimization Management 80

IBM Big Data Hub

JULY 17, 2023

Watsonx.data is built on 3 core integrated components: multiple query engines, a catalog that keeps track of metadata, and storage and relational data sources which the query engines directly access. AMC Networks is excited by the opportunity to capitalize on the value of all of their data to improve viewer experiences.

Machine Learning 64

Machine Learning Data Warehouse Modeling Cost-Benefit 64

Sisense

MAY 11, 2021

The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. According to a recent survey conducted by IDC , 43% of respondents were drawing intelligence from 10 to 30 data sources in 2020, with a jump to 64% in 2021!

Modeling 84

Modeling Big Data IoT Data Warehouse 84

CIO Business Intelligence

OCTOBER 11, 2022

What began as an initiative focused on R&D now has extended to the company’s three other major business units: Commercial, Operations, and Clinical, according to Kaur. Four ways to improve data-driven business transformation . Start small, think big, and scale fast. “You

Machine Learning 145

Machine Learning Data-driven Testing Data Science 145

CIO Business Intelligence

AUGUST 3, 2023

Model, understand, and transform the data Comcast faced the challenge of collecting large amounts of information about potential security and reliability issues but with no easy way to make sense of it all, says Noopur Davis, corporate EVP, CISO, and chief product privacy officer.

Analytics 94

Analytics Data Lake Metadata Cost-Benefit 94

Jet Global

FEBRUARY 23, 2024

This field guide to data mapping will explore how data mapping connects volumes of data for enhanced decision-making. Why Data Mapping is Important Data mapping is a critical element of any data management initiative, such as data integration, data migration, data transformation, data warehousing, or automation.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52