Octopai

SEPTEMBER 14, 2020

Modern data processing depends on metadata management to power enhanced business intelligence. Metadata is of course the information about the data, and the process of managing it is mysterious to those not trained in advanced BI. In this article, you will learn: What does metadata management do?

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Metadata Management Data Processing Machine Learning 52

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.). This also diminishes the value of data as an asset. Technical Metadata.

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Metadata Cost-Benefit Measurement Data-driven 132

Octopai

OCTOBER 5, 2021

An automated solution can collect, analyze, and organize – and then build or populate the data catalog by itself. Manual work is restricted to reviewing and enriching the catalog entries with missing descriptions, ratings, data owners, tags, etc. that have yet to be documented in any of the BI tools. Making Smart Choices.

Business Intelligence 84

Business Intelligence Software Cost-Benefit Metadata 84

Octopai

MAY 13, 2019

Many companies now struggle with their data because traditional approaches to managing it are increasingly inadequate. In this situation, control of an organization’s data becomes nearly impossible. That something has to do with metadata management. – Some see metadata management as a means to the end of data governance.

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Metadata Management Reporting Dashboards 40

erwin

APRIL 29, 2020

These tools range from enterprise service bus (ESB) products, data integration tools; extract, transform and load (ETL) tools, procedural code, application program interfaces (API)s, file transfer protocol (FTP) processes, and even business intelligence (BI) reports that further aggregate and transform data.

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Metadata Data Governance Key Performance Indicator Data Quality 111

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.

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Data Governance Risk Data Quality Dashboards 59

Octopai

JANUARY 19, 2020

BCBS 239 is a document published by that committee entitled, Principles for Effective Risk Data Aggregation and Risk Reporting. The document, first published in 2013, outlines best practices for global and domestic banks to identify, manage, and report risks, including credit, market, liquidity, and operational risks.

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Metadata Risk Management Business Intelligence Data Governance 61

CIO Business Intelligence

MAY 10, 2023

Without this important step, AI may produce inconsistent or inaccurate data that could put an organization in a risky gambit of leveraging insights that are not vetted. AI and NLP technology is now capable of processing both the request and the underlying results, enabling data to be interpreted and applied to business needs.

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Metadata Data Governance Modeling Technology 95

erwin

JANUARY 17, 2020

Data modeling is a process that enables organizations to discover, design, visualize, standardize and deploy high-quality data assets through an intuitive, graphical interface. Data models provide visualization, create additional metadata and standardize data design across the enterprise. What is Data Modeling?

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Data-driven Modeling Metadata Data Governance 138

CIO Business Intelligence

OCTOBER 13, 2023

Application data architect: The application data architect designs and implements data models for specific software applications. Information/data governance architect: These individuals establish and enforce data governance policies and procedures.

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Data Architecture Data Warehouse Statistics Visualization 126

datapine

SEPTEMBER 29, 2022

Therefore, there are several roles that need to be filled, including: DQM Program Manager: The program manager role should be filled by a high-level leader who accepts the responsibility of general oversight for business intelligence initiatives. The program manager should lead the vision for quality data and ROI.

Data Quality 241

Data Quality Metrics Data-driven Management 241

erwin

APRIL 27, 2022

Best Data Governance Solution (erwin Data Intelligence). Best Data Modeling Solution (erwin Data Modeler). Best Data Security Solution (Quest ApexSQL). Best Data Governance Solution (erwin Data Intelligence). Best Data Governance Solution (erwin Data Intelligence).

Data Governance 52

Data Governance Digital Transformation Metadata Data Warehouse 52

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 69

Analytics Data Warehouse Data Lake Metadata 69

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. One of the best ways to solve this issue is to create a business glossary. Automated Business Glossary Tools Streamline Processes.

Metadata 53

Metadata Data Warehouse Reporting Business Intelligence 53

Alation

DECEMBER 21, 2022

Transactional systems and data warehouses can then use the golden records as the entity’s most current, trusted representation. Data Catalog and Master Data Management. Early on, analysts used data catalogs to find and understand data more quickly. Having good data is crucial to creating golden records.

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Management Data Quality Metadata Testing 52

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.

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Data Quality Data Governance Metadata Metrics 98

Alation

FEBRUARY 13, 2020

This achievement is a testament not only to our legacy of helping to create the data catalog category but also to our continued innovation in improving the effectiveness of self-service analytics. A broader definition of Business Intelligence. Howard Dresner coined the term “Business Intelligence” in 1989.

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Business Intelligence Machine Learning Marketing Metadata 52

Alation

JUNE 28, 2022

This is where metadata, or the data about data, comes into play. Having a data catalog is the cornerstone of your data governance strategy, but what supports your data catalog? Your metadata management framework provides the underlying structure that makes your data accessible and manageable.

Metadata 52

Metadata Management Data Governance Machine Learning 52

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

Alation

APRIL 14, 2022

Semantics, context, and how data is tracked and used mean even more as you stretch to reach post-migration goals. This is why, when data moves, it’s imperative for organizations to prioritize data discovery. Data discovery is also critical for data governance , which, when ineffective, can actually hinder organizational growth.

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Metadata Data Governance Modeling Data-driven 59

CIO Business Intelligence

MARCH 6, 2024

SAP announced today a host of new AI copilot and AI governance features for SAP Datasphere and SAP Analytics Cloud (SAC). The company is expanding its partnership with Collibra to integrate Collibra’s AI Governance platform with SAP data assets to facilitate data governance for non-SAP data assets in customer environments. “We

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Unstructured Data Dashboards Business Intelligence Data Governance 110

erwin

MAY 27, 2020

What, then, should users look for in a data modeling product to support their governance/intelligence requirements in the data-driven enterprise? Nine Steps to Data Modeling. Provide metadata and schema visualization regardless of where data is stored.

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Modeling Metadata Data Governance Visualization 98

IBM Big Data Hub

OCTOBER 12, 2023

Among the tasks necessary for internal and external compliance is the ability to report on the metadata of an AI model. Metadata includes details specific to an AI model such as: The AI model’s creation (when it was created, who created it, etc.) And that makes sense.

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Cost-Benefit Metadata Data Governance Modeling 83

Octopai

JANUARY 12, 2020

From Data Analysts, BI Architects, Developers, and Data Governance Leaders to IT and BI Managers. If you’re in the Business Intelligence world, there is a chance that you and I had a brief chat about metadata. Here’s what I found: Data always tells the truth, even when it lies.

Metadata 57

Metadata Management Data Governance Reporting 57

erwin

SEPTEMBER 25, 2020

Understanding the benefits of data modeling is more important than ever. Data modeling is the process of creating a data model to communicate data requirements, documenting data structures and entity types. It has many benefits. Successfully design and implement databases. Foster successful cloud adoption.

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Modeling Cost-Benefit Visualization Metadata 111

AWS Big Data

JANUARY 22, 2024

The majority of data produced by these accounts is used downstream for business intelligence (BI) purposes and in Amazon Athena , by hundreds of business users every day. The solution Acast implemented is a data mesh, architected on AWS.

Data-driven 85

Data-driven Advertising Metadata Data Architecture 85

Alation

MARCH 21, 2023

What are common data challenges for the travel industry? Some companies struggle to optimize their data’s value and leverage analytics effectively. When companies lack a data governance strategy , they may struggle to identify all consumer data or flag personal data as subject to compliance audits.

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

Domino Data Lab

JULY 2, 2019

In other words, using metadata about data science work to generate code. In this case, code gets generated for data preparation, where so much of the “time and labor” in data science work is concentrated. Less data gets decompressed, deserialized, loaded into memory, run through the processing, etc.

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Metadata Machine Learning Data Science Data-driven 105

Alation

JANUARY 17, 2023

A typical modern data stack consists of the following: A data warehouse. Data ingestion/integration services. Data orchestration tools. Business intelligence (BI) platforms. These tools are used to manage big data, which is defined as data that is too large or complex to be processed by traditional means.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

Sisense

JULY 6, 2020

First off, this involves defining workflows for every business process within the enterprise: the what, how, why, who, when, and where aspects of data. These subsystems each play a vital part in your overall EDM program, but three that we’ll give special attention to are data governance, architecture, and warehousing.

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Enterprise Management Data Architecture Strategy 98

BI-Survey

FEBRUARY 23, 2023

Data knowledge is essential to data and analytics There is a clear understanding that data is an asset to the organization. Almost three quarters of respondents also state that they have recognized the need to invest in ways to access, link and understand metadata. These include tools for metadata management (e.g.,

Metadata 52

Metadata Data-driven Data Strategy Strategy 52

AWS Big Data

JUNE 9, 2023

Data in customers’ data lakes is used to fulfil a multitude of use cases, from real-time fraud detection for financial services companies, inventory and real-time marketing campaigns for retailers, or flight and hotel room availability for the hospitality industry.

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Data Lake Metadata Optimization Statistics 113

Alation

SEPTEMBER 23, 2021

What Is a Data Catalog? A data catalog is a centralized storage bank of metadata on information sources from across the enterprise, such as: Datasets. Business intelligence reports. The data catalog also stores metadata (data about data, like a conversation), which gives users context on how to use each asset.

Enterprise 52

Enterprise Metadata Data Governance Visualization 52

erwin

JUNE 27, 2019

Due to the amount of database platforms available, it’s important that an organization’s data modeling tool supports a sufficient (to your organization) array of platforms. The chosen data modeling tool should be able to read the technical formats of each of these platforms and translate them into highly graphical models rich in metadata.

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Measurement Modeling Unstructured Data Metadata 81

Alation

DECEMBER 15, 2021

Yet high-volume collection makes keeping that foundation sound a challenge, as the amount of data collected by businesses is greater than ever before. An effective data governance strategy is critical for unlocking the full benefits of this information. Data governance requires a system.

Data Governance 52

Data Governance Strategy Metadata Data Strategy 52

Grooper

OCTOBER 23, 2019

Lack of competitiveness or business losses seem to be the main drivers to becoming more proactive with data governance and management. What you’re shooting for is enterprise-wide information governance. Governance. Information governance is more than just ‘store everything!’ In Summary.

Metrics 59

Metrics Measurement Strategy Optimization 59

erwin

NOVEMBER 6, 2020

Prashant Parikh, erwin’s Senior Vice President of Software Engineering, talks about erwin’s vision to automate every aspect of the data governance journey to increase speed to insights. Although AI and ML are massive fields with tremendous value, erwin’s approach to data governance automation is much broader.

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Data Governance Metadata Data-driven Visualization 97