Alation

JANUARY 26, 2023

However, data needs to be easily accessible, usable, and secure to be useful — yet the opposite is too often the case. What’s worse, just 3% of the data in a business enterprise meets quality standards. There’s also no denying that data management is becoming more important, especially to the public.

Data Governance 52

Data Governance Strategy Data Quality Marketing 52

erwin

MARCH 8, 2019

GDPR) and to ensure peak business performance, organizations often bring consultants on board to help take stock of their data assets. This sort of data governance “stock check” is important but can be arduous without the right approach and technology. That’s where data governance comes in ….

Data Governance 65

Data Governance Metadata Data Warehouse Data Quality 65

erwin

JULY 2, 2020

Users discuss how they are putting erwin’s data modeling, enterprise architecture, business process modeling, and data intelligences solutions to work. IT Central Station members using erwin solutions are realizing the benefits of enterprise modeling and data intelligence. For Matthieu G., George H., Roshan H.,

Enterprise 122

Enterprise Modeling Metadata Data Governance 122

IBM Big Data Hub

JUNE 8, 2022

By taking advantage of data, enterprises can shape business decisions, minimize risk for stakeholders, and gain competitive advantage. Ensuring data quality and access within an organization, while establishing and maintaining proper governance processes, is a major struggle for many organizations.

Data-driven 58

Data-driven Enterprise Data Governance Data Lake 58

Laminar Security

JULY 19, 2023

Laminar Launches Two New Solutions to Become First Full Data Security Platform for Multi-Cloud and SaaS Environments In today’s data-driven world, cloud computing has become the backbone of innovation and growth for enterprises across all industries. Laminar’s forward-thinking approach addresses these requirements.

Data Warehouse 91

Data Warehouse Data-driven Data Governance Risk 91

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

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. Data architects are frequently part of a data science team and tasked with leading data system projects.

Data Architecture 132

Data Architecture Data Warehouse Statistics Visualization 132

CIO Business Intelligence

NOVEMBER 28, 2023

Still, to truly create lasting value with data, organizations must develop data management mastery. This means excelling in the under-the-radar disciplines of data architecture and data governance. The knock-on impact of this lack of analyst coverage is a paucity of data about monies being spent on data management.

Management 131

Management Data Architecture Data Lake Data Strategy 131

IBM Big Data Hub

APRIL 25, 2023

We also made the case that query and reporting, provided by big data engines such as Presto, need to work with the Spark infrastructure framework to support advanced analytics and complex enterprise data decision-making. 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

AWS Big Data

APRIL 29, 2024

Effective permission management helps tackle these challenges by controlling how data is accessed and used, providing data integrity and minimizing the risk of data breaches. Apache Ranger is a comprehensive framework designed for data governance and security in Hadoop ecosystems.

Management 83

Management Big Data Metadata Data Warehouse 83

CIO Business Intelligence

MARCH 6, 2024

The metrics you use to measure a cloud company are different than those you use to measure an enterprise license and maintenance company. This was a gift because it forced us into data governance and we sell data governance products, so this wasn’t a new concept to us. Look at changing metrics and KPIs as a gift.

Modeling 116

Modeling Management IT Metrics 116

David Menninger's Analyst Perspectives

NOVEMBER 30, 2021

It enables organizations to analyze streaming data in real time and provides the capability to automate analytics processes.

Analytics 160

Analytics Data Warehouse Business Intelligence Software 160

erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on. But the attempts to standardize data across the entire enterprise haven’t produced the desired results.

Data Governance 40

Data Governance Risk Metadata Management 40

AWS Big Data

SEPTEMBER 25, 2023

With Amazon Redshift , you can run a complex mix of workloads on your data warehouse, such as frequent data loads running alongside business-critical dashboard queries and complex transformation jobs. We also see more and more data science and machine learning (ML) workloads. ExampleCorp has multiple Redshift clusters.

Management 94

Management Data Warehouse Metrics Dashboards 94

Ontotext

MARCH 18, 2020

According to an article in Harvard Business Review , cross-industry studies show that, on average, big enterprises actively use less than half of their structured data and sometimes about 1% of their unstructured data. Why Enterprise Knowledge Graphs? The third challenge is how to combine data management with analytics.

Enterprise 59

Enterprise B2B Unstructured Data Machine Learning 59

Ontotext

MARCH 8, 2023

Use Case #1: Customer 360 / Enterprise 360 Customer data is typically spread across multiple applications, departments, and regions. Each team and system need to keep diverse sets of data about their customers in order to play their specific role – inadvertently leading to siloed experiences.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 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 71

Analytics Data Warehouse Data Lake Metadata 71

Timo Elliott

JANUARY 6, 2022

Like the proverbial man looking for his keys under the streetlight , when it comes to enterprise data, if you only look at where the light is already shining, you can end up missing a lot. If storage costs are escalating in a particular area, you may have found a good source of dark data. Data sense-making.

IT 133

IT Metadata Data-driven Data Governance 133

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

A data dictionary is a tool that organizes and describes different variables indicated by metadata associated with a dataset. A business glossary, sometimes referred to as a data glossary , is a broader tool. It defines terminology used by multiple departments across an enterprise. Get Good Stuff by Having a Data Dictionary.

Metadata 54

Metadata Enterprise Management Data Warehouse 54

Laminar Security

APRIL 18, 2023

The Addition of Google Cloud & Snowflake Support Make Laminar the First Cloud-native Data Security Platform to Fully Support Multi-cloud Architectures As cloud technologies continue to drive business innovation, organizations are turning to multi-cloud infrastructure to meet their diverse needs.

Data Warehouse 52

Data Warehouse Risk Cost-Benefit Structured Data 52

CIO Business Intelligence

FEBRUARY 16, 2023

Selling the value of data transformation Iyengar and his team are 18 months into a three- to five-year journey that started by building out the data layer — corralling data sources such as ERP, CRM, and legacy databases into data warehouses for structured data and data lakes for unstructured data.

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 105

Andrew White

DECEMBER 9, 2019

The outline of the call went as follows: I was taking to a central state agency who was organizing a data governance initiative (in their words) across three other state agencies. All four agencies had reported an independent but identical experience with data governance in the past. An expensive consulting engagement.

Analytics 66

Analytics Data Lake Data Governance Metadata 66

Cloudera

JANUARY 28, 2022

Then there are the more extensive discussions – scrutiny of the overarching, data strategy questions related to privacy, security, data governance /access and regulatory oversight. These are not straightforward decisions, especially when data breaches always hit the top of the news headlines.

Slice and Dice 109

Slice and Dice Cost-Benefit Risk Data Governance 109

CIO Business Intelligence

MAY 28, 2022

The key focus seems to be to eliminate the need for multiple vendors or platforms for data management and analytics, at a time when siloed data and the complexity of managing modern applications are plaguing enterprises. The announcements this week follow similar moves last year. It also has a partnership with Databricks.

Management 105

Management Data Warehouse Software Strategy 105

CIO Business Intelligence

MAY 27, 2022

The key focus seems to be to eliminate the need for multiple vendors or platforms for data management and analytics, at a time when siloed data and the complexity of managing modern applications are plaguing enterprises. The announcements this week follow similar moves last year. It also has a partnership with Databricks.

Management 105

Management Data Warehouse Software Strategy 105

CIO Business Intelligence

OCTOBER 13, 2022

In addition, the AWS and IBM joint Enterprise Transformation Program (ETP), aimed at large-scale transformation and modernization efforts, helps enterprise customers adopt new digital operating models structurally and prescriptively, and transform with AWS to deliver strategic business outcomes.

Insurance 115

Insurance Data Warehouse Manufacturing Forecasting 115

Alation

JULY 30, 2021

A part of that journey often involves moving fragmented on-premises data to a cloud data warehouse. You clearly shouldn’t move everything from your on-premises data warehouses. Otherwise, you can end up with a data swamp. 2: Biz Problem – Making Data Ready for Business Analysis.

Data Warehouse 52

Data Warehouse Data Governance Machine Learning Data-driven 52

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

Analytics Vidhya

OCTOBER 25, 2023

To steer growth, employ effective data management strategies and tools. This article explores data management’s key tool features and lists the top tools for 2023. These tools will serve as an asset to your enterprise workflow pipeline.

Management 208

Management Strategy Enterprise Analytics 208

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

erwin

APRIL 27, 2022

Best Data Governance Solution (erwin Data Intelligence). Best Data Modeling Solution (erwin Data Modeler). Best Data Security Solution (Quest ApexSQL). In data warehousing, the data is extracted and transported from production database(s) into a data warehouse for reporting and analysis.

Data Governance 52

Data Governance Digital Transformation Metadata Data Warehouse 52

Alation

DECEMBER 15, 2022

December 2012: Alation forms and goes to work creating the first enterprise data catalog. Later, in its inaugural report on data catalogs, Forrester Research recognizes that “Alation started the MLDC trend.”. October 2020: Forrester Research names Alation a Leader in The Forrester Wave: Machine Learning Data Catalogs, Q4, 2020.

Metadata 52

Metadata Data Governance Data Quality Marketing 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

IBM Big Data Hub

JANUARY 5, 2023

Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues. Several factors determine the quality of your enterprise data like accuracy, completeness, consistency, to name a few.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

Ontotext

NOVEMBER 16, 2023

Clarifying what data mesh is and how it works is important, but even more so is starting with the why. Why Organizations Need A Data Mesh The data mesh paradigm aims to address some of the biggest pain points for most organizations. This becomes particularly problematic when dealing with veracity of data.

Metadata 52

Metadata Data-driven Data Quality Data Architecture 52

Alation

JULY 28, 2022

But today, there is a magic quadrant for cloud databases and warehouses comprising more than 20 vendors. As enterprises migrate to the cloud, two key questions emerge: What’s driving this change? And what must organizations overcome to succeed at cloud data warehousing ? What Are the Biggest Drivers of Cloud Data Warehousing?

Data Warehouse 69

Data Warehouse Cost-Benefit Data Governance Data-driven 69