AWS Big Data

NOVEMBER 22, 2024

Common use cases for using the dbt adapter with Athena The following are common use cases for using the dbt adapter with Athena: Building a data warehouse – Many organizations are moving towards a data warehouse architecture, combining the flexibility of data lakes with the performance and structure of data warehouses.

Data Lake 103

Data Lake Data Warehouse Cost-Benefit Data Transformation 103

erwin

FEBRUARY 13, 2020

When an organization’s data governance and metadata management programs work in harmony, then everything is easier. Data governance is a complex but critical practice. Data Governance Attitudes Are Shifting. Data Governance Attitudes Are Shifting.

Metadata 135

Metadata Data Governance Management Cost-Benefit 135

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 122

Data Lake Data Warehouse Data Governance Publishing 122

AWS Big Data

AUGUST 15, 2024

Data quality is crucial in data pipelines because it directly impacts the validity of the business insights derived from the data. Today, many organizations use AWS Glue Data Quality to define and enforce data quality rules on their data at rest and in transit.

Data Quality 111

Data Quality Visualization Metadata Key Performance Indicator 111

DataKitchen

APRIL 13, 2021

We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . QuerySurge – Continuously detect data issues in your delivery pipelines. OwlDQ — Predictive data quality.

Testing 304

Testing Machine Learning Consulting Data Science 304

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 105

Metadata Data Governance Data Quality Data-driven 105

BI-Survey

FEBRUARY 17, 2020

From operational systems to support “smart processes”, to the data warehouse for enterprise management, to exploring new use cases through advanced analytics : all of these environments incorporate disparate systems, each containing data fragments optimized for their own specific task. .

Data Governance 89

Data Governance Data Warehouse Data Quality Data Strategy 89

AWS Big Data

JANUARY 15, 2025

Data landscape in EUROGATE and current challenges faced in data governance The EUROGATE Group is a conglomerate of container terminals and service providers, providing container handling, intermodal transports, maintenance and repair, and seaworthy packaging services. Eliminate centralized bottlenecks and complex data pipelines.

IoT 111

IoT Machine Learning Metadata Data-driven 111

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

erwin

MARCH 8, 2019

GDPR) and to ensure peak business performance, organizations often bring consultants on board to help take stock of their data assets. This sort of data governance “stock check” is important but can be arduous without the right approach and technology. That’s where data governance comes in ….

Data Governance 65

Data Governance Metadata Data Warehouse Data Quality 65

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 111

Data-driven Data Lake Data Quality Data Governance 111

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

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).

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

Alation

SEPTEMBER 7, 2021

In the previous blog , we discussed how Alation provides a platform for data scientists and analysts to complete projects and analysis at speed. In this blog we will discuss how Alation helps minimize risk with active data governance. So why are organizations not able to scale governance? Meet Governance Requirements.

Data Governance 59

Data Governance Risk Data Quality Dashboards 59

CIO Business Intelligence

OCTOBER 2, 2024

And with all the data an enterprise has to manage, it’s essential to automate the processes of data collection, filtering, and categorization. Many organizations have data warehouses and reporting with structured data, and many have embraced data lakes and data fabrics,” says Klara Jelinkova, VP and CIO at Harvard University.

Management 141

Management Data Governance Cost-Benefit Structured Data 141

Timo Elliott

JANUARY 6, 2022

If storage costs are escalating in a particular area, you may have found a good source of dark data. If you’ve been properly managing your metadata as part of a broader data governance policy, you can use metadata management explorers to reveal silos of dark data in your landscape. Data sense-making.

IT 135

IT Metadata Data-driven Data Governance 135

David Menninger's Analyst Perspectives

OCTOBER 2, 2024

Data as a product is the process of applying product thinking to data initiatives to ensure that the outcome —the data product—is designed to be shared and reused for multiple use cases across the business. A data contract should also define data quality and service-level key performance indicators and commitments.

Key Performance Indicator 130

Key Performance Indicator Data Governance Data Warehouse Enterprise 130

Alation

JANUARY 27, 2022

People might not understand the data, the data they chose might not be ideal for their application, or there might be better, more current, or more accurate data available. An effective data governance program ensures data consistency and trustworthiness. It can also help prevent data misuse.

Data Governance 52

Data Governance Analytics Cost-Benefit Data-driven 52

AWS Big Data

SEPTEMBER 11, 2024

This also includes building an industry standard integrated data repository as a single source of truth, operational reporting through real time metrics, data quality monitoring, 24/7 helpdesk, and revenue forecasting through financial projections and supply availability projections.

Data Architecture 111

Data Architecture Optimization Data Warehouse Metadata 111

AWS Big Data

DECEMBER 9, 2024

As organizations process vast amounts of data, maintaining an accurate historical record is crucial. History management in data systems is fundamental for compliance, business intelligence, data quality, and time-based analysis. Initialize the SparkSession with Iceberg settings.

Snapshot 64

Snapshot Data Warehouse Data Lake Data Quality 64

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

erwin

FEBRUARY 28, 2019

When you think of real-time, data-driven experiences and modern applications to accomplish tasks faster and easier, your local town or city government probably doesn’t come to mind. But municipal government is starting to embrace digital transformation and therefore data governance.

Digital Transformation 106

Digital Transformation Data Governance Data-driven Data Warehouse 106

erwin

DECEMBER 12, 2019

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

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. Set up unified data governance rules and processes.

Analytics 115

Analytics Key Performance Indicator Data Warehouse Data-driven 115

AWS Big Data

MARCH 7, 2023

Analytics reference architecture for gaming organizations In this section, we discuss how gaming organizations can use a data hub architecture to address the analytical needs of an enterprise, which requires the same data at multiple levels of granularity and different formats, and is standardized for faster consumption.

Analytics 96

Analytics Data Warehouse Data Lake Metadata 96

CIO Business Intelligence

OCTOBER 17, 2024

The data factor I joined Liberty Dental about two and a half years ago, and the first big opportunity I saw was data, which was all over the place. We had a kind of small data warehouse on-prem. We created our data model in a way that satisfied the requirements of what we had a vision of.

Management 111

Management Insurance ROI Cost-Benefit 111

erwin

JULY 17, 2019

Outsourcing these data management efforts to professional services firms only delays schedules and increases costs. With automation, data quality is systemically assured. The data pipeline is seamlessly governed and operationalized to the benefit of all stakeholders. Digital Transformation Strategy: Smarter Data.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

Alation

JANUARY 26, 2023

These data requirements could be satisfied with a strong data governance strategy. Governance can — and should — be the responsibility of every data user, though how that’s achieved will depend on the role within the organization. How can data engineers address these challenges directly?

Data Governance 52

Data Governance Strategy Data Quality Data Collection 52

datapine

FEBRUARY 22, 2022

This should also include creating a plan for data storage services. Are the data sources going to remain disparate? Or does building a data warehouse make sense for your organization? For this purpose, you can think about a data governance strategy. Clean data in, clean analytics out. Define a budget.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Dashboards 218

CIO Business Intelligence

DECEMBER 21, 2022

Stout, for instance, explains how Schellman addresses integrating its customer relationship management (CRM) and financial data. “A A lot of business intelligence software pulls from a data warehouse where you load all the data tables that are the back end of the different software,” she says. “Or

IT 131

IT Business Intelligence Sales Key Performance Indicator 131

AWS Big Data

MARCH 26, 2024

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data.

Data Strategy 98

Data Strategy Strategy Data Warehouse Prescriptive Analytics 98

Jet Global

FEBRUARY 5, 2019

It’s hard to answer that question because, truth be told, you don’t know you’re using bad data until it’s too late. . states that about 40 percent of enterprise data is either inaccurate, incomplete, or unavailable. Because bad data is the reason behind poor analytics. . Top 5 Warning Signs of Bad Data. Ted Friedman.

Data Warehouse 69

Data Warehouse Data Quality Business Intelligence Data Governance 69

AWS Big Data

MAY 7, 2024

Data governance is a key enabler for teams adopting a data-driven culture and operational model to drive innovation with data. Amazon DataZone allows you to simply and securely govern end-to-end data assets stored in your Amazon Redshift data warehouses or data lakes cataloged with the AWS Glue data catalog.

Metadata 107

Metadata Data Lake Data Processing Data-driven 107

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 Data Warehouse 105

Octopai

DECEMBER 12, 2021

How many different data systems do you have in your BI environment? The average data intelligence stack is comprised of the following components – ETL, data warehouse/database, analysis, and reporting – for each of which you may use one or multiple systems. Data catalogs. Metadata harvesting.

Metadata 98

Metadata Management Data Quality Data Governance 98

Jet Global

JANUARY 17, 2019

Here are 5 ways that MDM can help you better organize your Dynamics ERP data for BI and analytics: Simplifies Data Structure. With all of your data mapping to your master data, you get a more clear and controlled view of your operations and how you are performing. Develops Data Governance. Download Now.

Business Intelligence 75

Business Intelligence Management Data Warehouse Data Governance 75