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. In some ways, the data architect is an advanced data engineer.

Data Architecture 129

Data Architecture Data Warehouse Statistics Visualization 129

erwin

SEPTEMBER 10, 2020

Not Documenting End-to-End Data Lineage Is Risky Busines – Understanding your data’s origins is key to successful data governance. Not everyone understands what end-to-end data lineage is or why it is important. The risks of ignoring end-to-end data lineage are just too great.

Data Governance 131

Data Governance Key Performance Indicator Digital Transformation Metadata 131

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. Data Governance.

Metadata 111

Metadata Key Performance Indicator Data Governance Data Quality 111

AWS Big Data

MAY 23, 2024

AWS Glue , a serverless data integration service, simplifies the process of discovering, preparing, moving, and integrating data for analytics, machine learning (ML), and application development. This process is crucial for maintaining data integrity and avoiding duplication that could skew analytics and insights. cast('int')).drop("z_minScore",

Machine Learning 97

Machine Learning Interactive Recreation/Entertainment Data Integration 97

erwin

JANUARY 17, 2020

What is Data Modeling? 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.

Data-driven 138

Data-driven Modeling Metadata Data Governance 138

erwin

AUGUST 20, 2020

It provides a visual blueprint, demonstrating the connection between applications, technologies and data to the business functions they support. As a practice, EA involves the documentation, analysis, design and implementation of an organization’s assets and structure. Data Governance. Big Data Adoption.

Enterprise 140

Enterprise Cost-Benefit Risk Data Governance 140

erwin

AUGUST 7, 2019

Data cataloging helps curate internal and external datasets for a range of content authors. Gartner says this doubles business benefits and ensures effective management and monetization of data assets in the long-term if linked to broader data governance , data quality and metadata management initiatives.

Metadata 90

Metadata Data Governance Data Quality Data Warehouse 90

CIO Business Intelligence

NOVEMBER 21, 2023

Set parameters and emphasize collaboration To address one root cause of shadow IT, CIOs must also establish a governance and delivery model for evaluating, procuring, and implementing department technology solutions. There may be times when department-specific data needs and tools are required.

IT 133

IT Risk Cost-Benefit Risk Management 133

erwin

MARCH 1, 2022

You’ll see how erwin Data Modeler R12 makes it easy to: Find, visualize, design, deploy and standardize high-quality enterprise data assets. Discover and document any data from anywhere – all while supporting data governance and data intelligence efforts.

Modeling 52

Modeling Data Governance Visualization Enterprise 52

Octopai

MAY 15, 2023

Enhance data governance: Data lineage provides transparency into data flows, transformations, and dependencies, supporting robust data governance practices. It is also crucial to regularly review and update the lineage information as data and processes evolve over time.

Data Quality 52

Data Quality Data Governance Data Integration Risk 52

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.

Metadata 61

Metadata Risk Management Business Intelligence Data Governance 61

erwin

JULY 11, 2019

Planning and working toward a flexible, responsive and adaptable future is no longer enough – the modern organization must be able to visualize not only the end state (the infamous and so-elusive “to-be”) but also perform detailed and comprehensive impact analysis on each scenario, often in real time. Supporting and reference documentation.

Digital Transformation 106

Digital Transformation Modeling Data Governance Visualization 106

Octopai

JUNE 27, 2022

Your most technologically-challenged business user searches the data catalog at least once a week – without coming to you for help! Data catalog SUCCESS! Visualization may work wonders for athlete performance, but if you want to make data catalog adoption into a rousing success, you’re going to sweat a little bit.

Management 72

Management Metadata Visualization Data Governance 72

datapine

SEPTEMBER 29, 2022

He/she assists the organization by providing clarity and insight into advanced data technology solutions. As quality issues are often highlighted with the use of dashboard software , the change manager plays an important role in the visualization of data quality. Accuracy should be measured through source documentation (i.e.,

Data Quality 241

Data Quality Metrics Data-driven Management 241

Alation

JULY 19, 2021

This requires a metadata management solution to enable data search & discovery and data governance, both of which empower access to both the metadata and the underlying data to those who need it. In today’s world, metadata management best practices call for a data catalog. Administrative information.

Metadata 105

Metadata Management Data Governance Machine Learning 105

Alation

JUNE 2, 2022

In part one of this series, I discussed how data management challenges have evolved and how data governance and security have to play in such challenges, with an eye to cloud migration and drift over time. Data management is not yet a solved problem, but modern data management is leagues ahead of prior approaches.

Modeling 52

Modeling Data Governance Statistics Unstructured Data 52

CIO Business Intelligence

NOVEMBER 9, 2022

Have a data governance plan as well to validate and keep the metrics clean. Self-service enables all functions, including operations, finance, procurement, supply chain, and continuous improvement teams, to perform data discovery and create powerful visualizations. “We

Analytics 135

Analytics Slice and Dice Metrics Sales 135

Octopai

JULY 9, 2020

Here are some scenarios in which companies found real benefits from automated data lineage solutions: Data Lineage Enables Complex Data Processing Operations. By adopting automated data lineage and automated metadata tagging, companies have the opportunity to increase their data processing speed.

Insurance 86

Insurance Risk Management Machine Learning Metadata 86

erwin

OCTOBER 29, 2020

Automating data governance is key to addressing the exponentially growing volume and variety of data. Data readiness is everything. Earlier this year, erwin conducted a research project in partnership with Dataversity, the 2020 State of Data Governance and Automation.

Data Governance 105

Data Governance Metadata ROI Digital Transformation 105

Alation

FEBRUARY 20, 2020

Tools like MicroStrategy and Tableau make it easy for business users to quickly turn raw data into visualizations and reports. But before you can even start, you have to find a relevant data set, understand it, and trust it. Balanced Data Governance with MicroStrategy & Alation. abc/xyz, etc.).

Reporting 52

Reporting Dashboards Data Governance Visualization 52

Alation

DECEMBER 21, 2022

A data catalog is a metadata repository of information sources across the enterprise, including data sets, business intelligence reports, visualizations, and conversations. Early on, analysts used data catalogs to find and understand data more quickly. Having good data is crucial to creating golden records.

Management 52

Management Data Quality Metadata Testing 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 72

Analytics Data Warehouse Data Lake Metadata 72

Sisense

SEPTEMBER 12, 2019

You likely already have some form of scheduled reports, are drilling down into your data, discovering what is in your data, and may even be visualizing to some extent. 2 Plan your objectives (and map the supporting data). 3 Define how the data will be shared (and how it will be distributed).

Strategy 81

Strategy Dashboards Diagnostic Analytics Prescriptive Analytics 81

IBM Big Data Hub

JANUARY 8, 2024

This includes the overall system health as well as the ability to drill down into specifics of individual event payloads, schemas, publish and consumption rates and assists identification and resolution of any problematic event data. Governing an event-driven expansion Many organizations reach a point where use of events is expanding rapidly.

Data-driven 74

Data-driven Management Advertising Enterprise 74

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

Ontotext

MARCH 8, 2023

However, this information is typically stored in disparate locations, often hidden within departmental documents or applications. Yet, the biggest challenge for risk analysis continues to suffer from lack of a scalable way of understanding how data is interrelated.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

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.

Business Intelligence 84

Business Intelligence Software Cost-Benefit Metadata 84

erwin

MAY 27, 2020

And it exists across these hybrid architectures in different formats: big and unstructured and traditional structured business data may physically sit in different places. What’s desperately needed is a way to understand the relationships and interconnections between so many entities in data sets in detail.

Modeling 98

Modeling Metadata Data Governance Visualization 98

IBM Big Data Hub

FEBRUARY 26, 2024

The financial services industry has been in the process of modernizing its data governance for more than a decade. But as we inch closer to global economic downturn, the need for top-notch governance has become increasingly urgent. With data lineage, every object in the migrated system is mapped and dependencies are documented.

Cost-Benefit 92

Cost-Benefit Metadata Data Governance Reporting 92

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. In this post: What Is a Data Model? Why Is Data Modeling Important?

Modeling 111

Modeling Cost-Benefit Visualization Metadata 111

CIO Business Intelligence

FEBRUARY 20, 2023

A candidate who earns the certification will have proved their ability to build bundle configurations, pricing, output documents, and renewals and amendments. The consultant provides implementation, customization, and integration expertise in these technologies, as well as training and support.

Consulting 62

Consulting B2B Cost-Benefit Sales 62

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

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.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

DataKitchen

FEBRUARY 2, 2023

DataOps Automation (Orchestration, Environment Management, Deployment Automation) DataOps Observability (Monitoring, Test Automation) Data Governance (Catalogs, Lineage, Stewardship) Data Privacy (Access and Compliance) Data Team Management (Projects, Tickets, Documentation, Value Stream Management) What are the drivers of this consolidation?

Metadata 130

Metadata Testing Risk Data Science 130

IBM Big Data Hub

OCTOBER 12, 2023

Accounting for the complexities of the AI lifecycle Unfortunately, typical data storage and data governance tools fall short in the AI arena when it comes to helping an organization perform the tasks that underline efficient and responsible AI lifecycle management. And that makes sense.

Cost-Benefit 77

Cost-Benefit Metadata Data Governance Modeling 77

erwin

OCTOBER 4, 2021

What is known about the data and can be shared to extend data literacy within your organization. At its best, metadata management fuels enterprise data visibility, automation, data governance and collaboration across your enterprise. What should you look for in metadata management software?

Metadata 52

Metadata Software Management Visualization 52

Alation

OCTOBER 27, 2022

Few actors in the modern data stack have inspired the enthusiasm and fervent support as dbt. This data transformation tool enables data analysts and engineers to transform, test and document data in the cloud data warehouse. Next, we ingest the Google Sheet data into the Snowflake Data Cloud using Fivetran.

Metrics 52

Metrics Dashboards Sales Reporting 52