DataKitchen

APRIL 13, 2021

DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. It orchestrates complex pipelines, toolchains, and tests across teams, locations, and data centers. OwlDQ — Predictive data quality.

Testing 300

Testing Machine Learning Consulting Data Science 300

AWS Big Data

NOVEMBER 22, 2024

Now, with support for dbt Cloud, you can access a managed, cloud-based environment that automates and enhances your data transformation workflows. This upgrade allows you to build, test, and deploy data models in dbt with greater ease and efficiency, using all the features that dbt Cloud provides.

Data Lake 83

Data Lake Data Warehouse Cost-Benefit Data Transformation 83

AWS Big Data

AUGUST 15, 2024

Unifying these necessitates additional data processing, requiring each business unit to provision and maintain a separate data warehouse. This burdens business units focused solely on consuming the curated data for analysis and not concerned with data management tasks, cleansing, or comprehensive data processing.

Data Lake 108

Data Lake Data Warehouse Data Governance Publishing 108

AWS Big Data

OCTOBER 9, 2024

Today, customers are embarking on data modernization programs by migrating on-premises data warehouses and data lakes to the AWS Cloud to take advantage of the scale and advanced analytical capabilities of the cloud. Some customers build custom in-house data parity frameworks to validate data during migration.

Data Quality 95

Data Quality Data Lake Data Warehouse Metrics 95

AWS Big Data

JUNE 6, 2023

We are excited to announce the General Availability of AWS Glue Data Quality. Our journey started by working backward from our customers who create, manage, and operate data lakes and data warehouses for analytics and machine learning. It takes days for data engineers to identify and implement data quality rules.

Data Quality 97

Data Quality Statistics Data Lake Visualization 97

Jet Global

MAY 28, 2019

Whether the reporting is being done by an end user, a data science team, or an AI algorithm, the future of your business depends on your ability to use data to drive better quality for your customers at a lower cost. So, when it comes to collecting, storing, and analyzing data, what is the right choice for your enterprise?

Data Warehouse 85

Data Warehouse Reporting Business Intelligence Sales 85

DataKitchen

AUGUST 3, 2021

The past decades of enterprise data platform architectures can be summarized in 69 words. First-generation – expensive, proprietary enterprise data warehouse and business intelligence platforms maintained by a specialized team drowning in technical debt. DDD divides a system or model into smaller subsystems called domains.

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

Alation

JULY 28, 2022

It’s costly and time-consuming to manage on-premises data warehouses — and modern cloud data architectures can deliver business agility and innovation. However, CIOs declare that agility, innovation, security, adopting new capabilities, and time to value — never cost — are the top drivers for cloud data warehousing.

Data Warehouse 69

Data Warehouse Cost-Benefit Data-driven Data Governance 69

AWS Big Data

DECEMBER 4, 2024

Domain ownership recognizes that the teams generating the data have the deepest understanding of it and are therefore best suited to manage, govern, and share it effectively. This principle makes sure data accountability remains close to the source, fostering higher data quality and relevance.

Metadata 93

Metadata Data Governance Data Quality Data-driven 93

DataKitchen

SEPTEMBER 21, 2023

Data in Place refers to the organized structuring and storage of data within a specific storage medium, be it a database, bucket store, files, or other storage platforms. In the contemporary data landscape, data teams commonly utilize data warehouses or lakes to arrange their data into L1, L2, and L3 layers.

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

AWS Big Data

JANUARY 15, 2025

In addition to real-time analytics and visualization, the data needs to be shared for long-term data analytics and machine learning applications. To achieve this, EUROGATE designed an architecture that uses Amazon DataZone to publish specific digital twin data sets, enabling access to them with SageMaker in a separate AWS account.

IoT 100

IoT Machine Learning Metadata Data-driven 100

datapine

JANUARY 24, 2021

This can include a multitude of processes, like data profiling, data quality management, or data cleaning, but we will focus on tips and questions to ask when analyzing data to gain the most cost-effective solution for an effective business strategy. 4) How can you ensure data quality?

IT 317

IT Statistics KPI Data-driven 317

datapine

SEPTEMBER 27, 2022

Some of these ‘structures’ may include putting all the information; for instance, a structure could be about cars, placing them into tables that consist of makes, models, year of manufacture, and color. With a MySQL dashboard builder , for example, you can connect all the data with a few clicks. Viescas, Douglas J.

Business Intelligence 292

Business Intelligence Data Warehouse Data Processing Data mining 292

CIO Business Intelligence

MARCH 9, 2022

But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI. Traditional data warehouses, for example, support datasets from multiple sources but require a consistent data structure.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Big Data 119

IBM Big Data Hub

JANUARY 5, 2023

Poor data quality is one of the top barriers faced by organizations aspiring to be more data-driven. Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues.

Data Architecture 52

Data Architecture Data Quality Strategy Data Lake 52

CIO Business Intelligence

NOVEMBER 7, 2023

Centralized reporting boosts data value For more than a decade, pediatric health system Phoenix Children’s has operated a data warehouse containing more than 120 separate data systems, providing the ability to connect data from disparate systems. Companies should also incorporate data discovery, Higginson says.

Data Warehouse 142

Data Warehouse Digital Transformation Data-driven Reporting 142

AWS Big Data

JUNE 6, 2023

Poor-quality data can lead to incorrect insights, bad decisions, and lost opportunities. AWS Glue Data Quality measures and monitors the quality of your dataset. It supports both data quality at rest and data quality in AWS Glue extract, transform, and load (ETL) pipelines.

Data Quality 75

Data Quality Data Lake Visualization Data-driven 75

AWS Big Data

FEBRUARY 29, 2024

Data is your generative AI differentiator, and a successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Data governance is a critical building block across all these approaches, and we see two emerging areas of focus.

Data Governance 109

Data Governance Unstructured Data Metadata Data Lake 109

Smart Data Collective

JULY 9, 2023

ETL is a three-step process that involves extracting data from various sources, transforming it into a consistent format, and loading it into a target database or data warehouse. Extract The extraction phase involves retrieving data from diverse sources such as databases, spreadsheets, APIs, or other systems.

Data Quality 105

Data Quality Data Warehouse Data-driven Reporting 105

BI-Survey

APRIL 27, 2023

While most continue to struggle with data quality issues and cumbersome manual processes, best-in-class companies are making improvements with commercial automation tools. The data vault has strong adherents among best-in-class companies, even though its usage lags the alternative approaches of third-normal-form and star schema.

Modeling 52

Modeling Data Warehouse Data Quality Business Driver 52

AWS Big Data

AUGUST 1, 2024

Large-scale data warehouse migration to the cloud is a complex and challenging endeavor that many organizations undertake to modernize their data infrastructure, enhance data management capabilities, and unlock new business opportunities. This makes sure the new data platform can meet current and future business goals.

Data Warehouse 99

Data Warehouse KPI Optimization Cost-Benefit 99

Jet Global

JANUARY 20, 2021

Organizations that can effectively leverage data as a strategic asset will inevitably build a competitive advantage and outperform their peers over the long term. In order to achieve that, though, business managers must bring order to the chaotic landscape of multiple data sources and data models.

Data Analytics 95

Data Analytics Management Analytics Data Warehouse 95

erwin

FEBRUARY 19, 2021

A strong data management strategy and supporting technology enables the data quality the business requires, including data cataloging (integration of data sets from various sources), mapping, versioning, business rules and glossaries maintenance and metadata management (associations and lineage). Map data flows.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

AWS Big Data

FEBRUARY 27, 2024

The following are the key components of the Bluestone Data Platform: Data mesh architecture – Bluestone adopted a data mesh architecture, a paradigm that distributes data ownership across different business units. This enables data-driven decision-making across the organization.

Data-driven 106

Data-driven Data Lake Data Quality Data Governance 106

CIO Business Intelligence

DECEMBER 22, 2022

It seeks to improve the way data are managed and products are created, and to coordinate these improvements with the goals of the business. According to Gartner, DataOps also aims “to deliver value faster by creating predictable delivery and change management of data, data models, and related artifacts.”

Analytics 130

Analytics Machine Learning Data mining Software 130

Timo Elliott

JANUARY 6, 2022

The SAP Data Intelligence Cloud solution helps you simplify your landscape with tools for creating data pipelines that integrate data and data streams on the fly for any type of use – from data warehousing to complex data science projects to real-time embedded analytics in business applications.

IT 135

IT Metadata Data-driven Data Governance 135

Cloudera

AUGUST 31, 2021

Cloudera and Accenture demonstrate strength in their relationship with an accelerator called the Smart Data Transition Toolkit for migration of legacy data warehouses into Cloudera Data Platform. Accenture’s Smart Data Transition Toolkit . Are you looking for your data warehouse to support the hybrid multi-cloud?

Data Warehouse 82

Data Warehouse Cost-Benefit Metadata Data-driven 82

erwin

JULY 17, 2019

Part Two of the Digital Transformation Journey … In our last blog on driving digital transformation , we explored how enterprise architecture (EA) and business process (BP) modeling are pivotal factors in a viable digital transformation strategy. With automation, data quality is systemically assured.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

AWS Big Data

NOVEMBER 9, 2023

The aim was to bolster their analytical capabilities and improve data accessibility while ensuring a quick time to market and high data quality, all with low total cost of ownership (TCO) and no need for additional tools or licenses. dbt emerged as the perfect choice for this transformation within their existing AWS environment.

Data Warehouse 118

Data Warehouse Testing Data Quality Reporting 118

David Menninger's Analyst Perspectives

OCTOBER 2, 2024

The format of the outcome is not a defining characteristic of the data product, which could be a business intelligence (BI) dashboard (and the underlying data warehouse), a decision intelligence application, an algorithm or artificial intelligence/machine learning (AI/ML) model, or a custom-built operational application.

Key Performance Indicator 130

Key Performance Indicator Data Governance Data Warehouse Enterprise 130

CIO Business Intelligence

OCTOBER 2, 2024

According to Kari Briski, VP of AI models, software, and services at Nvidia, successfully implementing gen AI hinges on effective data management and evaluating how different models work together to serve a specific use case. But some IT leaders are getting it right because they focus on three key aspects.

Management 141

Management Data Governance Cost-Benefit Structured Data 141

erwin

AUGUST 7, 2019

A data catalog benefits organizations in a myriad of ways. With the right data catalog tool, organizations can automate enterprise metadata management – including data cataloging, data mapping, data quality and code generation for faster time to value and greater accuracy for data movement and/or deployment projects.

Metadata 90

Metadata Data Governance Data Quality Data Warehouse 90

Smart Data Collective

SEPTEMBER 26, 2021

There’s not much value in holding on to raw data without putting it to good use, yet as the cost of storage continues to decrease, organizations find it useful to collect raw data for additional processing. The raw data can be fed into a database or data warehouse. If it’s not done right away, then later.

Metadata 130

Metadata Visualization Unstructured Data Data mining 130

CIO Business Intelligence

MARCH 22, 2022

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. Another option is a data warehouse, which stores processed and refined data. Ready to evolve your analytics strategy or improve your data quality?

Analytics 115

Analytics Key Performance Indicator Data Warehouse Data-driven 115

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 96

Enterprise Data Warehouse Snapshot Cost-Benefit 96

Smart Data Collective

OCTOBER 13, 2021

As we have already said, the challenge for companies is to extract value from data, and to do so it is necessary to have the best visualization tools. Over time, it is true that artificial intelligence and deep learning models will be help process these massive amounts of data (in fact, this is already being done in some fields).

Visualization 145

Visualization Cost-Benefit Big Data Prescriptive Analytics 145

erwin

MARCH 8, 2019

Following are two examples that illustrate the data governance stock check, including the Any 2 approach in action, based on real consulting engagements. Therefore, the organization needed to catalog the data it acquires from suppliers, ensure its quality, classify it, and then sell it to customers.

Data Governance 65

Data Governance Metadata Data Warehouse Data Quality 65