Alation

JUNE 2, 2022

These include tracking, documenting, monitoring, versioning, and controlling access to AI/ML models. Currently, models are managed by modelers and by the software tools they use, which results in a patchwork of control, but not on an enterprise level. How Data Lineage Is a Use Case in ML. from cognilytica.

Modeling 52

Modeling Data Governance Statistics Unstructured Data 52

erwin

DECEMBER 3, 2020

The answer is radical transformation, made possible by an intelligent, data-driven approach to: New business models. One Customer’s Journey to Controlling Data Chaos. Being able to integrate all data touchpoints, including erwin DM for data modeling, Denodo for data visualization, and Jira for ticketing, has been key.

Metadata 141

Metadata Data Governance Data-driven Digital Transformation 141

Ontotext

NOVEMBER 18, 2021

And all of them are asking hard questions: “Can you integrate my data, with my particular format?”, “How well can you scale?”, “How many visualizations do you offer?”. Nowadays, data analytics doesn’t exist on its own. You have to take care of data extraction, transformation and loading, and of visualization.

Visualization 98

Visualization Reporting Metadata Enterprise 98

IBM Big Data Hub

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

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

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. Assess Data Quality.

Management 52

Management Data Quality Metadata Testing 52

Ontotext

SEPTEMBER 15, 2020

The Data Fabric paradigm combines design principles and methodologies for building efficient, flexible and reliable data management ecosystems. Knowledge Graphs are the Warp and Weft of a Data Fabric. To implement any Data Fabric approach, it is essential to be able to understand the context of data.

Metadata 69

Metadata Knowledge Discovery Data Quality Strategy 69

AWS Big Data

FEBRUARY 1, 2023

The response times for these data sources are critical to our key stakeholders. Therefore, we must take a data-driven approach to select a high-performance architecture. Storage and redundancy – Due to the heterogeneous data stores and models, it was challenging to store the different datasets from various business stakeholder teams.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

Octopai

MAY 31, 2022

On the occasions when a report or dashboard error does show up, it doesn’t take long to do some BI root cause analysis and track down the source of the error using a data lineage visualization. Bonus tool: active metadata management. An active metadata management tool adds a maître d’ to self-serve analytics.

Management 52

Management Metadata Business Intelligence ROI 52

IBM Big Data Hub

MAY 9, 2022

Others have come into sharper focus relatively recently: a global effort to create new data privacy laws, a post-pandemic expectation by customers to know them individually across all touchpoints, and increased attention on any racial, gender-based, or socioeconomic bias in AI models. million each year [1] and $1.2 28, 2021. [2].

Management 57

Management Data Quality Metadata Data Integration 57

AWS Big Data

JUNE 14, 2023

We’ve made a big impact with QuickSight because it doesn’t require in-depth knowledge about data visualizations to build dashboards and provide insights, empowering our users to build what they need. This dashboard helps our operations team and end customers improve the data quality of key attribution and reduce manual intervention.

Dashboards 74

Dashboards KPI Scorecard Consulting 74

AWS Big Data

MARCH 7, 2023

Sources Data can be loaded from multiple sources, such as systems of record, data generated from applications, operational data stores, enterprise-wide reference data and metadata, data from vendors and partners, machine-generated data, social sources, and web sources.

Analytics 70

Analytics Data Warehouse Data Lake Metadata 70

IBM Big Data Hub

JULY 13, 2023

When we talk about data integrity, we’re referring to the overarching completeness, accuracy, consistency, accessibility, and security of an organization’s data. Together, these factors determine the reliability of the organization’s data. Data quality Data quality is essentially the measure of data integrity.

Data Quality 66

Data Quality Data Integration Metadata Cost-Benefit 66

Ontotext

JUNE 22, 2023

On top of that, data is sometimes unreliable , and inaccurate or missing metadata makes it hard to decide which information to trust. The data model can adapt effortlessly to the iterative development of use cases across different therapeutic areas.

Metrics 52

Metrics Statistics Visualization Metadata 52

Ontotext

MARCH 8, 2023

With the size of data and dropping attention spans of online users, digital personalization has become one of the top priorities for companies’ business models. Graph-based solutions further leverage the relationships among the entities involved to create a semantically enhanced machine learning model. million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

AWS Big Data

NOVEMBER 16, 2023

As with all AWS services, Amazon Redshift is a customer-obsessed service that recognizes there isn’t a one-size-fits-all for customers when it comes to data models, which is why Amazon Redshift supports multiple data models such as Star Schemas, Snowflake Schemas and Data Vault.

Enterprise 82

Enterprise Data Warehouse Snapshot Cost-Benefit 82

BI-Survey

FEBRUARY 6, 2020

ML helps users prepare data to enhance reports and to select appropriate data visualizations in visual analysis and dashboards. Data management has always been a challenge for companies. Data quality is seldomly handled in source systems in a way that meets the needs of decision support.

Reporting 59

Reporting Optimization Enterprise Data Quality 59

DataKitchen

SEPTEMBER 21, 2023

These layers help teams delineate different stages of data processing, storage, and access, offering a structured approach to data management. In the context of Data in Place, validating data quality automatically with Business Domain Tests is imperative for ensuring the trustworthiness of your data assets.

Testing 176

Testing Data Quality Predictive Modeling Metrics 176

erwin

MAY 27, 2020

Data modeling supports collaboration among business stakeholders – with different job roles and skills – to coordinate with business objectives. Data resides everywhere in a business , on-premise and in private or public clouds. A single source of data truth helps companies begin to leverage data as a strategic asset.

Modeling 98

Modeling Metadata Data Governance Visualization 98

Alation

JULY 19, 2022

Across the country, data scientists have an unemployment rate of 2% and command an average salary of nearly $100,000. As they attempt to put machine learning models into production, data science teams encounter many of the same hurdles that plagued data analytics teams in years past: Finding trusted, valuable data is time-consuming.

Metadata 59

Metadata Data Quality Statistics Data Science 59

Smart Data Collective

SEPTEMBER 26, 2021

Everyone has to manage raw data at one point or another; yet, not everybody stores it in a way that’s useful for further analysis or comparison to other data sets. As data sets become bigger, it becomes harder to visualize information. Draw a chart highlighting each endpoint in your data. Speaking of which.

Metadata 98

Metadata Visualization Unstructured Data Data mining 98

erwin

OCTOBER 29, 2020

Whether driving digital experiences, mapping customer journeys, enhancing digital operations, developing digital innovations, finding new ways to interact with customers, or building digital ecosystems or marketplaces – all of this digital transformation is powered by data. The State of Data Automation.

Data Governance 105

Data Governance Metadata Digital Transformation ROI 105

IBM Big Data Hub

OCTOBER 12, 2023

Connecting AI models to a myriad of data sources across cloud and on-premises environments AI models rely on vast amounts of data for training. Once trained and deployed, models also need reliable access to historical and real-time data to generate content, make recommendations, detect errors, send proactive alerts, etc.

Cost-Benefit 81

Cost-Benefit Metadata Data Governance Modeling 81

CIO Business Intelligence

DECEMBER 21, 2022

BI software helps companies do just that by shepherding the right data into analytical reports and visualizations so that users can make informed decisions. To gain employee buy-in, Stout’s team builds BI dashboards to show them how they can easily connect to and interact with their data, as well as visualize it in a meaningful way.

IT 126

IT Business Intelligence Sales Key Performance Indicator 126

IBM Big Data Hub

APRIL 27, 2022

Gartner defines a data fabric as “a design concept that serves as an integrated layer of data and connecting processes. The data fabric architectural approach can simplify data access in an organization and facilitate self-service data consumption at scale.

Management 85

Management Metadata Data Architecture Data Lake 85

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

erwin

MARCH 21, 2019

With business process modeling (BPM) being a key component of data governance , choosing a BPM tool is part of a dilemma many businesses either have or will soon face. Historically, BPM didn’t necessarily have to be tied to an organization’s data governance initiative. Choosing a BPM Tool: An Overview. Silo Buster.

Modeling 75

Modeling Metadata IT Data Governance 75

Andrew White

JANUARY 11, 2021

Where does the Data Architect role fits in the Operational Model ? Assuming a data architect helps model and guide and assist D&A then they play a key role. As such any Data and Analytics strategy needs to incorporate data sovereignty as per of its D&A governance program. Try some gamification?

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

Alation

JUNE 21, 2022

Analysts didn’t just want to catalog data sources, they wanted to include dashboards, reports, and visualizations. Why start with a data source and build a visualization, if you can just find a visualization that already exists, complete with metadata about it? Data engineers want to catalog data pipelines.

Metadata 52

Metadata Data Quality Visualization Data Lake 52

Smart Data Collective

OCTOBER 13, 2021

There are countless examples of big data transforming many different industries. It can be used for something as visual as reducing traffic jams, to personalizing products and services, to improving the experience in multiplayer video games. We would like to talk about data visualization and its role in the big data movement.

Visualization 133

Visualization Cost-Benefit Big Data Prescriptive Analytics 133

datapine

JANUARY 31, 2022

BI software uses algorithms to extract actionable insights from a company’s data and guide its strategic decisions. BI users analyze and present data in the form of dashboards and various types of reports to visualize complex information in an easier, more approachable way.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

erwin

JANUARY 3, 2020

While these will remain big data governance trends for 2020, we anticipate organizations will finally begin tapping into the true value of data as the foundation of the digital business model. Data Modeling: Drive Business Value and Underpin Governance with an Enterprise Data Model.

Data Governance 139

Data Governance Digital Transformation IoT Metadata 139

DataKitchen

AUGUST 8, 2023

On 20 July 2023, Gartner released the article “ Innovation Insight: Data Observability Enables Proactive Data Quality ” by Melody Chien. It alerts data and analytics leaders to issues with their data before they multiply. It alerts data and analytics leaders to issues with their data before they multiply.

Data Quality 130

Data Quality Testing Snapshot Reporting 130

erwin

JANUARY 3, 2020

While these will remain big data governance trends for 2020, we anticipate organizations will finally begin tapping into the true value of data as the foundation of the digital business model. Data Modeling: Drive Business Value and Underpin Governance with an Enterprise Data Model.

Data Governance 52

Data Governance Digital Transformation IoT Metadata 52

BI-Survey

MARCH 4, 2022

Important action items are: Define responsibilities around data with special attention to improving data quality and breaking up data silos, two of the most severe inhibitors of a positive data culture, and even digitalization as a whole. Enable the company-wide availability of conformed KPIs and data products.

Data-driven 52

Data-driven Data Strategy Data Governance Strategy 52

Alation

FEBRUARY 17, 2023

Reichental describes data governance as the overarching layer that empowers people to manage data well ; as such, it is focused on roles & responsibilities, policies, definitions, metrics, and the lifecycle of the data. In this way, data governance is the business or process side.

Data Governance 52

Data Governance Data Quality Metadata Cost-Benefit 52

erwin

AUGUST 1, 2023

Intro erwin ® Data Modeler 12.5 Because of the ability to provide standardization and foundational stability through all these processes, data modeling is a crucial step to success, and erwin ® Data Modeler by Quest ® is celebrating its 30 th birthday by releasing its newest, most collaborative version to date.

Modeling 52

Modeling Metadata Data Quality Data Governance 52