Alation

SEPTEMBER 7, 2021

In this blog we will discuss how Alation helps minimize risk with active data governance. Now that you have empowered data scientists and analysts to access the Snowflake Data Cloud and speed their modeling and analysis, you need to bolster the effectiveness of your governance models. Find Trusted Data.

Data Governance 59

Data Governance Risk Data Quality Dashboards 59

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 Quality.

Metadata 111

Metadata Data Governance Key Performance Indicator Data Quality 111

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

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

IBM Big Data Hub

APRIL 10, 2023

A well-designed data architecture should support business intelligence and analysis, automation, and AI—all of which can help organizations to quickly seize market opportunities, build customer value, drive major efficiencies, and respond to risks such as supply chain disruptions.

Strategy 87

Strategy Data Architecture Cost-Benefit Reporting 87

Octopai

MAY 31, 2022

If your data management enables you to breathe a sigh of relief (as opposed to jumping for joy), that’s a good sign that it’s managing data as a liability. In contrast, data management for BI is asset management. Business intelligence is the primary place where your data becomes an asset.

Management 52

Management Metadata Business Intelligence ROI 52

CIO Business Intelligence

MARCH 9, 2022

They conveniently store data in a flat architecture that can be queried in aggregate and offer the speed and lower cost required for big data analytics. On the other hand, they don’t support transactions or enforce data quality. Each ETL step risks introducing failures or bugs that reduce data quality. .

Data Lake 94

Data Lake Unstructured Data Data Warehouse Data Quality 94

CIO Business Intelligence

NOVEMBER 22, 2022

As a result, a growing number of IT leaders are looking for data strategies that will allow them to manage the massive amounts of disparate data located in silos without introducing new risk and compliance challenges. The fabric, especially at the active metadata level, is important, Saibene notes.

Data Strategy 145

Data Strategy Strategy Enterprise Consulting 145

Alation

DECEMBER 15, 2021

This uncovers actionable intelligence, maintains compliance with regulations, and mitigates risks. Let’s explore the key steps for building an effective data governance strategy. What is a Data Governance Strategy? Data governance focuses on the daily tasks that keep information usable, understandable, and protected.

Data Governance 52

Data Governance Strategy Metadata Data Strategy 52

CIO Business Intelligence

APRIL 29, 2022

Preparing for an artificial intelligence (AI)-fueled future, one where we can enjoy the clear benefits the technology brings while also the mitigating risks, requires more than one article. This first article emphasizes data as the ‘foundation-stone’ of AI-based initiatives. Establishing a Data Foundation. era is upon us.

Data Governance 140

Data Governance IT Risk Data Lake 140

Alation

OCTOBER 21, 2021

Data lakes also support the growing thirst for analysis by data scientists and data analysts, as well as the critical role of data governance. But setting up a data lake takes a thoughtful approach to ensure it’s positioned to prevent it from becoming a data swamp. Lack of metadata. Ungoverned data.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

IBM Big Data Hub

MARCH 14, 2024

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.

Cost-Benefit 77

Cost-Benefit Metadata Optimization Management 77

Ontotext

JULY 6, 2023

This shift of both a technical and an outcome mindset allows them to establish a centralized metadata hub for their data assets and effortlessly access information from diverse systems that previously had limited interaction. There are four groups of data that are naturally siloed: Structured data (e.g.,

Cost-Benefit 52

Cost-Benefit Metadata Experimentation Risk 52

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.)

Cost-Benefit 77

Cost-Benefit Metadata Data Governance Modeling 77

CIO Business Intelligence

MARCH 4, 2024

To deliver a cohesive data strategy, seamless data access and sharing requires the breaking down of data silos. This is where data fabric tools with their focus on orchestration, contextual layering, and metadata management are important elements to add to the equation.

Insurance 77

Insurance Strategy Data Governance Data Integration 77

AWS Big Data

JULY 20, 2023

Orca Security is an industry-leading Cloud Security Platform that identifies, prioritizes, and remediates security risks and compliance issues across your AWS Cloud estate. Moreover, running advanced analytics and ML on disparate data sources proved challenging. Amazon SageMaker is used to build, train, and deploy a range of ML models.

Data Lake 89

Data Lake Analytics Snapshot Optimization 89

Jet Global

FEBRUARY 23, 2024

The quick and dirty definition of data mapping is the process of connecting different types of data from various data sources. Data mapping is a crucial step in data modeling and can help organizations achieve their business goals by enabling data integration, migration, transformation, and quality.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

Alation

AUGUST 26, 2021

What Is Data Intelligence? Data intelligence is a system to deliver trustworthy, reliable data. It includes intelligence about data, or metadata. IDC coined the term, stating, “data intelligence helps organizations answer six fundamental questions about data.”

Metadata 64

Metadata Data Governance Dashboards Software 64

CIO Business Intelligence

JANUARY 30, 2024

Birgit Fridrich, who joined Allianz as sustainability manager responsible for ESG reporting in late 2022, spends many hours validating data in the company’s Microsoft Sustainability Manager tool. Data quality is key, but if we’re doing it manually there’s the potential for mistakes.

Reporting 93

Reporting Data Quality Strategy Data-driven 93

Alation

MARCH 21, 2023

Data security The travel industry collects, transmits, processes, and stores a wide range of personally identifiable information (PII) from customers, which are of interest to bad actors, as cybercriminals target this valuable data. Otherwise, they risk a data privacy violation.

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

Cloudera

AUGUST 31, 2021

Today, modern data warehousing has evolved to meet the intensive demands of the newest analytics required for a business to be data driven. Traditional data warehouse vendors may have maturity in data storage, modeling, and high-performance analysis. Consideration of both data & metadata in the migration.

Data Warehouse 82

Data Warehouse Cost-Benefit Metadata Data-driven 82

IBM Big Data Hub

AUGUST 4, 2023

By leveraging data services and APIs, a data fabric can also pull together data from legacy systems, data lakes, data warehouses and SQL databases, providing a holistic view into business performance. It uses knowledge graphs, semantics and AI/ML technology to discover patterns in various types of metadata.

Data Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59

AWS Big Data

MARCH 1, 2024

One of the bank’s key challenges related to strict cybersecurity requirements is to implement field level encryption for personally identifiable information (PII), Payment Card Industry (PCI), and data that is classified as high privacy risk (HPR). Only users with required permissions are allowed to access data in clear text.

Data Lake 101

Data Lake Data Warehouse Management Risk 101

Alation

APRIL 12, 2022

On the one hand, facilitating access to data through data democratization allows a company to become more data driven and derive more value from its data. More people can connect to useful data faster, and IT doesn’t have to play data middleman to the masses. Improving Data Quality.

Data Quality 52

Data Quality Data Governance Metrics Data Strategy 52

AWS Big Data

AUGUST 14, 2023

At the same time, unstructured approaches to data mesh management that don’t have a vision for what types of products should exist and how to ensure they are developed are at high risk of creating the same effect through simple neglect. When do new data products get created, and who is allowed to create them?

Management 81

Management Risk Measurement Optimization 81

Octopai

JULY 12, 2020

GIGO may be an old refrain, but it likely gave rise to the concept of what we know as ‘business intelligence’. BI has helped enhance a company’s ability to process large amounts of data. Perhaps most frustrating for FCSA was the major data-quality issues that arose due to manual, error-prone data processing.

Data Warehouse 58

Data Warehouse Data Quality Metadata Risk Management 58

Jet Global

JULY 2, 2019

Ungoverned or uncatalogued data can leave businesses vulnerable both in terms of data quality (and organizational trust in that data), as well as in terms of security, regulatory, and compliance risks. Build your Business Intelligence Infrastructure on a Solid Foundation.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

Andrew White

MARCH 22, 2019

to weave together the governance and management of master data, application data, and less-widely shared data, and just enough enterprise metadata management. Your Future Requires You to Define Your Real Master Data. Don’t You Need to Understand Your Business Information Architecture?

Analytics 68

Analytics Metadata Data Governance Management 68

Peter James Thomas

AUGUST 29, 2018

However, in reality, the CDO role encompasses Enterprise Data Management, although generally speaking the EDM role includes responsibility for the day to day operations of the collection processes, which in my current role I don’t have. Helping organisations become “data-centric” is a key part of what you do.

Data-driven 61

Data-driven Cost-Benefit Metadata Technology 61

Domino Data Lab

JULY 22, 2019

But the business logic kept getting more and more progressively rolled back into the middle layer, also called application servers, web servers, later being called middleware. Then in the bottom tier, you had your data management, your back office, right? You see these drivers involving risk and cost, but also opportunity.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109