CIO Business Intelligence

OCTOBER 1, 2022

The digital transformation of P&G’s manufacturing platform will enable the company to check product quality in real-time directly on the production line, maximize the resiliency of equipment while avoiding waste, and optimize the use of energy and water in manufacturing plants.

Manufacturing 145

Manufacturing Digital Transformation IoT Internet of Things 145

AWS Big Data

JUNE 28, 2023

They can connect to multiple data streams and pull data directly into Amazon Redshift without staging it in Amazon Simple Storage Service (Amazon S3). After running analytics, the insights can be made available broadly across the organization with Amazon QuickSight , a cloud-native, serverless business intelligence service.

Analytics 71

Analytics Data Warehouse Data Lake Data-driven 71

erwin

OCTOBER 8, 2020

The desire to modernize technology, over time, leads to acquiring many different systems with various data entry points and transformation rules for data as it moves into and across the organization. The metadata-driven suite automatically finds, models, ingests, catalogs and governs cloud data assets.

Data Governance 145

Data Governance Metadata Testing Data Lake 145

CIO Business Intelligence

FEBRUARY 16, 2023

Selling the value of data transformation Iyengar and his team are 18 months into a three- to five-year journey that started by building out the data layer — corralling data sources such as ERP, CRM, and legacy databases into data warehouses for structured data and data lakes for unstructured data.

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 105

AWS Big Data

AUGUST 31, 2023

Amazon Redshift is a fast, fully managed petabyte-scale cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. Amazon Redshift also supports querying nested data with complex data types such as struct, array, and map.

Data Lake 97

Data Lake Data Warehouse Metadata Data Architecture 97

CIO Business Intelligence

APRIL 29, 2022

This would be straightforward task were it not for the fact that, during the digital-era, there has been an explosion of data – collected and stored everywhere – much of it poorly governed, ill-understood, and irrelevant. Further, data management activities don’t end once the AI model has been developed. Addressing the Challenge.

Data Governance 145

Data Governance IT Risk Data Lake 145

CIO Business Intelligence

AUGUST 2, 2023

Historically, we drove productivity through Lean Six Sigma and optimizing workflows. we’re putting sensors across our manufacturing processes, which give us vast sums of data our leaders use to rethink those processes. These aren’t typically business discussions; it’s largely IT. But with the advent of Industry 4.0,

Manufacturing 96

Manufacturing Data Architecture Strategy Data Strategy 96

IBM Big Data Hub

DECEMBER 16, 2022

For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance. It uses metadata and data management tools to organize all data assets within your organization. So, Alex and other business analysts could complete their projects faster.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

Jet Global

OCTOBER 7, 2020

In the future, customers will be able to deploy Data Entities and replicate transactional tables in an Azure Data Lake. This includes the ability to drill down through live D365 F&SCM data through balances, journal entries, and into subledger transactions to find and fix data integrity and reconciliation issues fast.

Data Warehouse 90

Data Warehouse OLAP Reporting Finance 90

AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. In this post, we describe Orca’s journey building a transactional data lake using Amazon Simple Storage Service (Amazon S3), Apache Iceberg, and AWS Analytics.

Data Lake 89

Data Lake Analytics Snapshot Optimization 89

AWS Big Data

NOVEMBER 13, 2023

Amazon Redshift enables you to use SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes, using AWS-designed hardware and machine learning (ML) to deliver the best price-performance at scale. These upstream data sources constitute the data producer components.

Data Warehouse 95

Data Warehouse Data Lake Analytics Data Science 95

AWS Big Data

JULY 13, 2023

This post discusses the journey that took Altron from their initial goals, to technical implementation, to the business value created from understanding their customers and their unique opportunities better. Foundations for a data lake with data governance controls and data quality checks.

Optimization 92

Optimization B2B Data Quality Sales 92

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 104

Data Warehouse Data Lake Analytics Machine Learning 104

AWS Big Data

MAY 3, 2023

In today’s data-driven business environment, organizations face the challenge of efficiently preparing and transforming large amounts of data for analytics and data science purposes. Businesses need to build data warehouses and data lakes based on operational data.

Data Lake 83

Data Lake Data Warehouse Data-driven Optimization 83

AWS Big Data

NOVEMBER 29, 2023

Of course, the value of a strong data foundation is not new and the need for one spans well beyond generative AI. You also need services to store data for analysis and machine learning (ML) like Amazon Simple Storage Service (Amazon S3). Customers have created hundreds of thousands of data lakes on Amazon S3.

Data Warehouse 111

Data Warehouse Data Lake Data Integration Dashboards 111

AWS Big Data

NOVEMBER 30, 2023

In this post, we explore how to use the AWS Glue native connector for Teradata Vantage to streamline data integrations and unlock the full potential of your data. Businesses often rely on Amazon Simple Storage Service (Amazon S3) for storing large amounts of data from various data sources in a cost-effective and secure manner.

IT 100

IT Visualization Machine Learning Data Integration 100

CIO Business Intelligence

FEBRUARY 22, 2024

Consider your overall IT strategy to maximize your investment “Existing relationships with vendors may have some relevance as well in easing the implementation and data integration requirements,” says IDC’s Craven. That’s where the single source of truth comes into perspective and increases performance,” Karcher says.

Software 93

Software Reporting KPI Enterprise 93

IBM Big Data Hub

OCTOBER 12, 2023

To maximize the business outcomes that can come from using AI while also controlling costs and reducing inherent AI complexities, organizations need to combine AI-optimized data storage capabilities with a data governance program exclusively made for AI. But the implementation of AI is only one piece of the puzzle.

Cost-Benefit 79

Cost-Benefit Metadata Data Governance Modeling 79

CIO Business Intelligence

SEPTEMBER 22, 2023

All this data arrives by the terabyte, and a data management platform can help marketers make sense of it all. DMPs excel at negotiating with a wide array of databases, data lakes, or data warehouses, ingesting their streams of data and then cleaning, sorting, and unifying the information therein.

Management 105

Management Advertising Data Lake Sales 105

CIO Business Intelligence

MARCH 22, 2022

Which type(s) of storage consolidation you use depends on the data you generate and collect. . One option is a data lake—on-premises or in the cloud—that stores unprocessed data in any type of format, structured or unstructured, and can be queried in aggregate. Set up unified data governance rules and processes.

Analytics 111

Analytics Key Performance Indicator Data Warehouse Data-driven 111

AWS Big Data

MARCH 3, 2023

Additionally, the scale is significant because the multi-tenant data sources provide a continuous stream of testing activity, and our users require quick data refreshes as well as historical context for up to a decade due to compliance and regulatory demands. Finally, data integrity is of paramount importance.

Software 52

Software Data Lake Testing Cost-Benefit 52

AWS Big Data

FEBRUARY 21, 2023

Loading complex multi-point datasets into a dimensional model, identifying issues, and validating data integrity of the aggregated and merged data points are the biggest challenges that clinical quality management systems face. What is a dimensional data model? It optimizes the database for faster data retrieval.

Data Warehouse 66

Data Warehouse Data Lake Cost-Benefit Modeling 66

CIO Business Intelligence

JUNE 9, 2022

All this data arrives by the terabyte, and a data management platform can help marketers make sense of it all. Marketing-focused or not, DMPs excel at negotiating with a wide array of databases, data lakes, or data warehouses, ingesting their streams of data and then cleaning, sorting, and unifying the information therein.

Management 144

Management Advertising Data Lake Sales 144

AWS Big Data

NOVEMBER 13, 2023

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Analytics 113

Analytics Data Lake Data Warehouse Data-driven 113

AWS Big Data

NOVEMBER 29, 2023

We have seen a strong customer demand to expand its scope to cloud-based data lakes because data lakes are increasingly the enterprise solution for large-scale data initiatives due to their power and capabilities. The team uses dbt-glue to build a transformed gold model optimized for business intelligence (BI).

Data Lake 107

Data Lake Management Metrics Data Warehouse 107

IBM Big Data Hub

AUGUST 4, 2023

By leveraging data services and APIs, a data fabric can also pull together data from legacy systems, data lakes, data warehouses and SQL databases, providing a holistic view into business performance. Then, it applies these insights to automate and orchestrate the data lifecycle.

Data Architecture 62

Data Architecture Data Lake Machine Learning Data Governance 62

Jet Global

MAY 9, 2024

Data pipelines are designed to automate the flow of data, enabling efficient and reliable data movement for various purposes, such as data analytics, reporting, or integration with other systems. 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

FEBRUARY 23, 2024

Data mapping is essential for integration, migration, and transformation of different data sets; it allows you to improve your data quality by preventing duplications and redundancies in your data fields. Data mapping helps standardize, visualize, and understand data across different systems and applications.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

Jet Global

SEPTEMBER 30, 2022

Understandably, optimizing cloud investment remains a top priority to ensure your company does not fall behind. What are the best practices for analyzing cloud ERP data? Data Management. How do we create a data warehouse or data lake in the cloud using our cloud ERP? Self-service BI.

Reporting 52

Reporting Data Warehouse Operational Reporting Enterprise 52