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

Alation

AUGUST 9, 2022

Today, data is more valuable to a company than it’s ever been. It can help you make data-driven decisions which can improve business performance, boost revenue, and improve efficiencies. This can cause anything from day-to-day issues to significant business problems and risks. What is data integrity?

Data Integration 52

Data Integration Data Quality Measurement Strategy 52

erwin

JANUARY 9, 2020

Enterprises are trying to manage data chaos. They also face increasing regulatory pressure because of global data regulations , such as the European Union’s General Data Protection Regulation (GDPR) and the new California Consumer Privacy Act (CCPA), that went into effect last week on Jan. GDPR: Key Differences.

Data Governance 144

Data Governance Modeling Metadata Unstructured Data 144

Alation

JANUARY 27, 2022

How do businesses transform raw data into competitive insights? Data analytics. As an organization embraces digital transformation , more data is available to inform decisions. To use that data, decision-makers across the company will need to have access. It can also help prevent data misuse. Value and Challenges.

Data Governance 52

Data Governance Analytics Cost-Benefit Data-driven 52

erwin

FEBRUARY 4, 2021

Better decision-making has now topped compliance as the primary driver of data governance. However, organizations still encounter a number of bottlenecks that may hold them back from fully realizing the value of their data in producing timely and relevant business insights. Points of integration. Sources, like IoT.

Data Governance 89

Data Governance Metadata Data Quality Risk Management 89

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.

Data Governance 97

Data Governance Metadata Data-driven Visualization 97

Octopai

JUNE 26, 2020

We’re dealing with data day in and day out, but if isn’t accurate then it’s all for nothing!” Steve needed a robust and automated metadata management solution as part of his organization’s data governance strategy. Enterprise data governance. Metadata in data governance.

Metadata 84

Metadata Data Governance Enterprise Reporting 84

erwin

JANUARY 24, 2019

Organizations are responsible for governing more data than ever before, making a strong automation framework a necessity. In most companies, an incredible amount of data flows from multiple sources in a variety of formats and is constantly being moved and federated across a changing system landscape. Governing metadata.

Data Governance 71

Data Governance Metadata Data-driven Cost-Benefit 71

Alation

OCTOBER 28, 2021

Healthcare is changing, and it all comes down to data. Data & analytics represents a major opportunity to tackle these challenges. Indeed, many healthcare organizations today are embracing digital transformation and using data to enhance operations. In other words, they use data to heal more people and save more lives.

Data Governance 52

Data Governance Measurement Metrics Modeling 52

BI-Survey

FEBRUARY 17, 2020

Data is everywhere. With the growing interconnectedness of people, companies and devices, we are now accumulating increasing amounts of data from a growing variety of channels. New data (or combinations of data) enable innovative use cases and assist in optimizing internal processes.

Data Governance 89

Data Governance Data Warehouse Data Quality Data Strategy 89

CIO Business Intelligence

JANUARY 24, 2024

Organizations can’t afford to mess up their data strategies, because too much is at stake in the digital economy. How enterprises gather, store, cleanse, access, and secure their data can be a major factor in their ability to meet corporate goals. Here are some data strategy mistakes IT leaders would be wise to avoid.

Data Strategy 130

Data Strategy Strategy Unstructured Data Data Governance 130

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

FineReport

APRIL 9, 2024

Understanding Healthcare BI Tools The Role of Healthcare BI Tools Healthcare BI tools are instrumental in revolutionizing decision-making processes and patient care through the utilization of advanced data analysis and technology.

Digital Transformation 52

Digital Transformation Business Intelligence Data-driven Visualization 52

IBM Big Data Hub

JUNE 29, 2023

Integrated planning incorporates supply chain planning, demand planning, and demand forecasts so the company can quickly assess the impact on inventory levels, supply chain logistics, production plans, and customer service capacity. Data integration and analytics IBP relies on the integration of data from different sources and systems.

Key Performance Indicator 76

Key Performance Indicator Forecasting Data Integration Sales 76

CIO Business Intelligence

NOVEMBER 21, 2023

Ask IT leaders about their challenges with shadow IT, and most will cite the kinds of security, operational, and integration risks that give shadow IT its bad rep. That’s not to downplay the inherent risks of shadow IT. There may be times when department-specific data needs and tools are required.

IT 124

IT Risk Cost-Benefit Risk Management 124

Cloudera

JUNE 22, 2023

These dis-integrated resources are “data platforms” in name only: in addition to their high maintenance costs, their lack of interoperability with other critical systems makes it difficult to respond to business change. The top-line benefits of a hybrid data platform include: Cost efficiency. Simplified compliance. Flexibility.

Cost-Benefit 66

Cost-Benefit Digital Transformation Data Governance Unstructured Data 66

FineReport

APRIL 9, 2024

Evolving BI Tools in 2024 Significance of Business Intelligence In 2024, the role of business intelligence software tools is more crucial than ever, with businesses increasingly relying on data analysis for informed decision-making.

Business Intelligence 52

Business Intelligence Software Data-driven Predictive Modeling 52

erwin

APRIL 29, 2020

Data lineage is the journey data takes from its creation through its transformations over time. Tracing the source of data is an arduous task. With all these diverse data sources, and if systems are integrated, it is difficult to understand the complicated data web they form much less get a simple visual flow.

Metadata 111

Metadata Data Governance Key Performance Indicator Data Quality 111

erwin

JULY 17, 2019

EA and BP modeling squeeze risk out of the digital transformation process by helping organizations really understand their businesses as they are today. Once you’ve determined what part(s) of your business you’ll be innovating — the next step in a digital transformation strategy is using data to get there. Probably not.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

DataRobot

JANUARY 20, 2022

The following is a summary list of the key data-related priorities facing ICSs during 2022 and how we believe the combined Snowflake & DataRobot AI Cloud Platform stack can empower the ICS teams to deliver on these priorities. Key Data Challenges for Integrated Care Systems in 2022. Building data communities.

Data-driven 145

Data-driven Experimentation Modeling Predictive Modeling 145

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 77

Cost-Benefit Metadata Data Governance Modeling 77

Alation

JULY 28, 2022

The cloud is no longer synonymous with risk. There was a time when most CIOs would never consider putting their crown jewels — AKA customer data and associated analytics — into the cloud. 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

IBM Big Data Hub

OCTOBER 30, 2023

In today’s digital age where data stands as a prized asset, generative AI serves as the transformative tool to mine its potential. Businesses globally recognize the power of generative AI and are eager to harness data and AI for unmatched growth, sustainable operations, streamlining and pioneering innovation.

Insurance 79

Insurance Data Warehouse Data-driven Unstructured Data 79

DataKitchen

NOVEMBER 18, 2021

For several years now, the elephant in the room has been that data and analytics projects are failing. Gartner estimated that 85% of big data projects fail. Add all these facts together, and it paints a picture that something is amiss in the data world. . The top-line result was that 97% of data engineers are feeling burnout. .

Testing 246

Testing Data Governance Measurement Software 246

CDW Research Hub

JANUARY 28, 2022

In today’s data-driven world, your storage architecture must be able to store, protect and manage all sources and types of data while scaling to manage the exponential growth of data created by IoT, videos, photos, files, and apps. Flash storage and NVMe remove bottlenecks from workloads across the data center.

Digital Transformation 86

Digital Transformation Data-driven IoT Optimization 86

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

FEBRUARY 19, 2021

Metadata management is key to wringing all the value possible from data assets. However, most organizations don’t use all the data at their disposal to reach deeper conclusions about how to drive revenue, achieve regulatory compliance or accomplish other strategic objectives. Quite simply, metadata is data about data.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

IBM Big Data Hub

AUGUST 4, 2023

Data democratization, much like the term digital transformation five years ago, has become a popular buzzword throughout organizations, from IT departments to the C-suite. It’s often described as a way to simply increase data access, but the transition is about far more than that. What is data democratization?

Data Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59

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

AWS Big Data

MARCH 26, 2024

This view is used to identify patterns and trends in customer behavior, which can inform data-driven decisions to improve business outcomes. In this post, we discuss how you can use purpose-built AWS services to create an end-to-end data strategy for C360 to unify and govern customer data that address these challenges.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

Jet Global

FEBRUARY 29, 2024

Additionally, the manual nature of the approval process increases the risk of delays and inaccuracies, further complicating the budgeting workflow. 3) Data Fragmentation and Inconsistency Large organizations often grapple with disparate, ungoverned data sets scattered across various spreadsheets and systems.

Forecasting 52

Forecasting Reporting Data-driven Software 52

Alation

FEBRUARY 10, 2022

Data classification is necessary for leveraging data effectively and efficiently. Effective data classification helps mitigate risk, maintain governance and compliance, improve efficiencies, and help businesses understand and better use data. Manual Data Classification. Manual Data Classification.

Data Governance 52

Data Governance Risk Insurance Strategy 52

IBM Big Data Hub

OCTOBER 20, 2023

AI platform tools enable knowledge workers to analyze data, formulate predictions and execute tasks with greater speed and precision than they can manually. AI platforms assist with a multitude of tasks ranging from enforcing data governance to better workload distribution to the accelerated construction of machine learning models.

Machine Learning 72

Machine Learning Manufacturing Cost-Benefit Deep Learning 72

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

erwin

MAY 14, 2021

compliance with the General Data Protection Regulation). Accelerating the retrieval and analysis of data —so much of it unstructured—is vital to becoming a data-driven business that can effectively respond in real time to customers, partners, suppliers and other parties, and profit from these efforts.

Modeling 80

Modeling Digital Transformation Data-driven Optimization 80

Ontotext

MARCH 8, 2023

Gartner predicts that graph technologies will be used in 80% of data and analytics innovations by 2025, up from 10% in 2021. Use Case #1: Customer 360 / Enterprise 360 Customer data is typically spread across multiple applications, departments, and regions. Several factors are driving the adoption of knowledge graphs. million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 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