datapine

SEPTEMBER 29, 2022

1) What Is Data Quality Management? 4) Data Quality Best Practices. 5) How Do You Measure Data Quality? 6) Data Quality Metrics Examples. 7) Data Quality Control: Use Case. 8) The Consequences Of Bad Data Quality. 9) 3 Sources Of Low-Quality Data. 10) Data Quality Solutions: Key Attributes.

Data Quality 241

Data Quality Metrics Data-driven Management 241

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

MAY 28, 2022

New partnerships with Oracle, Microsoft Azure and Google Cloud are highlighting Informatica’s strategy to dominate the market for data management products by offering integrations that cut down the time and complexity of data migration, management and engineering tasks. Informatica eyes data management dominance.

Management 105

Management Data Warehouse Software Strategy 105

CIO Business Intelligence

MAY 27, 2022

New partnerships with Oracle, Microsoft Azure and Google Cloud are highlighting Informatica’s strategy to dominate the market for data management products by offering integrations that cut down the time and complexity of data migration, management and engineering tasks. Informatica eyes data management dominance.

Management 105

Management Data Warehouse Software Strategy 105

CIO Business Intelligence

OCTOBER 13, 2023

Data architect role Data architects are senior visionaries who translate business requirements into technology requirements and define data standards and principles, often in support of data or digital transformations. They often report to data infrastructure and data science leads.

Data Architecture 132

Data Architecture Data Warehouse Statistics Visualization 132

IBM Big Data Hub

APRIL 25, 2023

In a prior blog , we pointed out that warehouses, known for high-performance data processing for business intelligence, can quickly become expensive for new data and evolving workloads. To do so, Presto and Spark need to readily work with existing and modern data warehouse infrastructures.

Optimization 57

Optimization Strategy Data Warehouse Cost-Benefit 57

Alation

DECEMBER 21, 2022

Master Data Management (MDM) and data catalog growth are accelerating because organizations must integrate more systems, comply with privacy regulations, and address data quality concerns. What Is Master Data Management (MDM)? Data Catalog and Master Data Management. Conclusion.

Management 52

Management Data Quality Metadata Testing 52

AWS Big Data

MARCH 7, 2023

Decoupled and scalable – Serverless, auto scaled, and fully managed services are preferred over manually managed services. A data hub is a center of data exchange that constitutes a hub of data repositories and is supported by data engineering, data governance, security, and monitoring services.

Analytics 72

Analytics Data Warehouse Data Lake Metadata 72

IBM Big Data Hub

JANUARY 5, 2023

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases. Reduce data duplication and fragmentation.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

erwin

APRIL 27, 2022

Best Data Governance Solution (erwin Data Intelligence). Best Data Modeling Solution (erwin Data Modeler). Best Data Security Solution (Quest ApexSQL). This award is especially significant because the winning information management solutions are chosen by the people who use them.

Data Governance 52

Data Governance Digital Transformation Metadata Data Warehouse 52

CIO Business Intelligence

FEBRUARY 16, 2023

My vision is that I can give the keys to my businesses to manage their data and run their data on their own, as opposed to the Data & Tech team being at the center and helping them out,” says Iyengar, director of Data & Tech at Straumann Group North America. The offensive side?

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 105

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

Octopai

FEBRUARY 12, 2020

Like any good puzzle, metadata management comes with a lot of complex variables. That’s why you need to use data dictionary tools, which can help organize your metadata into an archive that can be navigated with ease and from which you can derive good information to power informed decision-making. . Why Have a Data Dictionary? #1

Metadata 54

Metadata Enterprise Management Data Warehouse 54

Jet Global

FEBRUARY 5, 2019

But data has become increasingly complex, with high volumes from different sources spanning across multiple geographic regions. While we’ve seen a rise in technology investment that manages business processes and gathers data, it has greatly exceeded the time and resources put towards data management and governance.

Data Quality 69

Data Quality Data Warehouse Business Intelligence Data Governance 69

AWS Big Data

MARCH 10, 2023

One important feature is to run different workloads such as business intelligence (BI), Machine Learning (ML), Data Science and data exploration, and Change Data Capture (CDC) of transactional data, without having to maintain multiple copies of data.

Data Lake 105

Data Lake Sales Data Warehouse Snapshot 105

CIO Business Intelligence

OCTOBER 13, 2022

Such an approach ensures that app modernization efforts meet any relevant certification requirements and solve business-specific problems. The goal of transformation is not just to become more modern, but to change the way companies adapt to the new norms of running a business in the digital world.”. Application Management

Insurance 115

Insurance Data Warehouse Manufacturing Forecasting 115

erwin

JUNE 26, 2020

It’s no surprise that most organizations’ data is often fragmented and siloed across numerous sources (e.g., legacy systems, data warehouses, flat files stored on individual desktops and laptops, and modern, cloud-based repositories.). Clearly documents data catalog policies, rules and shares information assets.

Metadata 132

Metadata Cost-Benefit Measurement Data-driven 132

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. Protected and compliant data. Speed and self-service.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

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 52

Metadata Data Governance Digital Transformation Data Quality 52

Jet Global

JULY 2, 2019

The sheer scale of data being captured by the modern enterprise has necessitated a monumental shift in how that data is stored. From the humble database through to data warehouses , data stores have grown both in scale and complexity to keep pace with the businesses they serve, and the data analysis now required to remain competitive.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

Octopai

DECEMBER 10, 2019

Well, scoot over Templeton, because it’s also going to be the year of the Automated Business Glossary for business intelligence and data governance teams everywhere. Automated Business Glossary Tools Streamline Processes. According to the Chinese Zodiac, 2020 is the year of the rat.

Metadata 53

Metadata Data Warehouse Reporting Business Intelligence 53

TDAN

MAY 31, 2022

As we enter a new cloud-first era, advancements in technology have helped companies capture and capitalize on data as much as possible. Deciding between which cloud architecture to use has always been a debate between two options: data warehouses and data lakes.

Data Lake 52

Data Lake Data Warehouse Technology Data Architecture 52

BizAcuity

APRIL 1, 2023

Thanks to the recent technological innovations and circumstances to their rapid adoption, having a data warehouse has become quite common in various enterprises across sectors. However, many businesses seem to face a lot of challenges, which includes ensuring a ‘single source of truth’ across the organization.

Business Intelligence 52

Business Intelligence Consulting KPI Data Warehouse 52

BizAcuity

JANUARY 31, 2023

Thanks to the recent technological innovations and circumstances to their rapid adoption, having a data warehouse has become quite common in various enterprises across sectors. However, many businesses seem to face a lot of challenges, which includes ensuring a ‘single source of truth’ across the organization.

Business Intelligence 52

Business Intelligence Consulting KPI Data Warehouse 52

FineReport

MAY 31, 2023

Furthermore, we will introduce some business intelligence solution that excels in simplifying the process of creating and utilizing a financial dashboard effectively. The balance sheet plays a vital role in internal management, helping companies fine-tune their business strategies and prevent misuse.

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

Birst BI

JANUARY 23, 2018

Data governance is a broad topic that people seem to agree is important, but still argue about the details. Data semantics are everything. Many IT and data management professionals posit that a single central data repository, such as a large cloud data warehouse or a data lake, is the definitive “single version of the truth.”

Data Warehouse 50

Data Warehouse Data Governance Data Lake Enterprise 50

CIO Business Intelligence

JUNE 14, 2023

The certification focuses on the seven domains of the analytics process: business problem framing, analytics problem framing, data, methodology selection, model building, deployment, and lifecycle management. It requires completion of the CAP exam and adherence to the CAP Code of Ethics.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

Alation

MAY 24, 2022

generally available on May 24, Alation introduces the Open Data Quality Initiative for the modern data stack, giving customers the freedom to choose the data quality vendor that’s best for them with the added confidence that those tools will integrate seamlessly with Alation’s Data Catalog and Data Governance application.

Data Quality 98

Data Quality Data Governance Metadata Metrics 98

Domino Data Lab

APRIL 3, 2019

Paco Nathan ‘s latest column dives into data governance. This month’s article features updates from one of the early data conferences of the year, Strata Data Conference – which was held just last week in San Francisco. In particular, here’s my Strata SF talk “Overview of Data Governance” presented in article form.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Cloudera

SEPTEMBER 23, 2022

In short, just like on-premise deployments, a small team of operaitons personnel are required to successfully deploy and manage this type of data lakehouse deployment. . Cost : PaaS data lakehouses run in your cloud account. The CDP One data lakehouse is continuously monitored for availability.

Data Governance 104

Data Governance Strategy Enterprise Cost-Benefit 104

Jet Global

JANUARY 17, 2019

In today’s data-driven world, business intelligence (BI) and analytics play a huge role in better understanding your customers, improving your operations, and making actionable business decisions. Take a look at the data you need to use in order to get any value from business intelligence and analytics.

Business Intelligence 75

Business Intelligence Management Data Warehouse Data Governance 75

Domino Data Lab

JULY 22, 2019

data science’s emergence as an interdisciplinary field – from industry, not academia. why data governance, in the context of machine learning is no longer a “dry topic” and how the WSJ’s “global reckoning on data governance” is potentially connected to “premiums on leveraging data science teams for novel business cases”.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

CIO Business Intelligence

DECEMBER 21, 2022

Every day, organizations of every description are deluged with data from a variety of sources, and attempting to make sense of it all can be overwhelming. So a strong business intelligence (BI) strategy can help organize the flow and ensure business users have access to actionable business insights. “By

IT 131

IT Business Intelligence Sales Key Performance Indicator 131

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 77

Metadata Data Lake Data Processing Data-driven 77

BI-Survey

AUGUST 21, 2020

But what are the right measures to make the data warehouse and BI fit for the future? Can the basic nature of the data be proactively improved? The following insights came from a global BARC survey into the current status of data warehouse modernization. They are opting for cloud data services more frequently.

Data Warehouse 98

Data Warehouse Data Lake Data Governance Data Architecture 98

Alation

JANUARY 17, 2023

It is known to have benefits in handling data due to its robustness, speed, and scalability. A typical modern data stack consists of the following: A data warehouse. Data ingestion/integration services. Data orchestration tools. Business intelligence (BI) platforms. Better Data Culture.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

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