Alation

JANUARY 27, 2022

People might not understand the data, the data they chose might not be ideal for their application, or there might be better, more current, or more accurate data available. An effective data governance program ensures data consistency and trustworthiness. It can also help prevent data misuse.

Data Governance 52

Data Governance Analytics Cost-Benefit Data-driven 52

Alation

JANUARY 20, 2022

In Ryan’s “9-Step Process for Better Data Quality” he discussed the processes for generating data that business leaders consider trustworthy. To be clear, data quality is one of several types of data governance as defined by Gartner and the Data Governance Institute. Step 4: Data Sources.

Data Quality 94

Data Quality Data Governance Metrics Statistics 94

BI-Survey

FEBRUARY 17, 2020

Data and data management processes are everywhere in the organization so there is a growing need for a comprehensive view of business objects and data. It is therefore vital that data is subject to some form of overarching control, which should be guided by a data strategy. This is where data governance comes in.

Data Governance 89

Data Governance Data Warehouse Data Quality Data Strategy 89

Alation

OCTOBER 28, 2021

This data is also a lucrative target for cyber criminals. Healthcare leaders face a quandary: how to use data to support innovation in a way that’s secure and compliant? Data governance in healthcare has emerged as a solution to these challenges. Uncover intelligence from data. Protect data at the source.

Data Governance 52

Data Governance Measurement Metrics Modeling 52

CIO Business Intelligence

FEBRUARY 2, 2024

Certifications measure your knowledge and skills against industry- and vendor-specific benchmarks to prove to employers you have the right skillset. The credential is available at the executive management, principal, mastery, associate practitioner, and foundation assistant data governance professional levels.

Management 113

Management Data Governance Cost-Benefit Testing 113

Cloudera

FEBRUARY 15, 2024

From stringent data protection measures to complex risk management protocols, institutions must not only adapt to regulatory shifts but also proactively anticipate emerging requirements, as well as predict negative outcomes.

Insurance 86

Insurance Data Architecture Risk Management Risk 86

DataKitchen

NOVEMBER 18, 2021

In our survey, data engineers cited the following as causes of burnout: The relentless flow of errors. Restrictive data governance Policies. For see the entire results of the data engineering survey, please visit “ 2021 Data Engineering Survey: Burned-Out Data Engineers are Calling for DataOps.”.

Testing 246

Testing Data Governance Measurement Software 246

O'Reilly on Data

JANUARY 29, 2019

A recent survey investigated how companies are approaching their AI and ML practices, and measured the sophistication of their efforts. In order to have a longstanding AI and ML practice, companies need to have data infrastructure in place to collect, transform, store, and manage data.

Deep Learning 207

Deep Learning Machine Learning Data Science Metadata 207

IBM Big Data Hub

JANUARY 9, 2024

Currently, no standardized process exists for overcoming data ingestion’s challenges, but the model’s accuracy depends on it. Increased variance: Variance measures consistency. Insufficient data can lead to varying answers over time, or misleading outliers, particularly impacting smaller data sets.

Enterprise 75

Enterprise Data Integration Data Quality Contextual Data 75

IBM Big Data Hub

JUNE 29, 2023

Data integration and analytics IBP relies on the integration of data from different sources and systems. This may involve consolidating data from enterprise resource planning (ERP) systems, customer relationship management (CRM) systems, supply chain management systems, and other relevant sources.

Key Performance Indicator 80

Key Performance Indicator Forecasting Data Integration Sales 80

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

Challenges in Data Management Data Security and Compliance The protection of sensitive patient information and adherence to regulatory standards pose significant challenges in healthcare data management. Quality assurance measures play a pivotal role in validating the accuracy and relevance of data utilized by BI tools.

Digital Transformation 52

Digital Transformation Business Intelligence Data-driven Visualization 52

Cloudera

JUNE 22, 2023

It ensures compliance with regulatory requirements while shifting non-sensitive data and workloads to the cloud. Its built-in intelligence automates common data management and data integration tasks, improves the overall effectiveness of data governance, and permits a holistic view of data across the cloud and on-premises environments.

Cost-Benefit 66

Cost-Benefit Digital Transformation Data Governance Unstructured Data 66

DataKitchen

APRIL 13, 2021

We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . QuerySurge – Continuously detect data issues in your delivery pipelines. Process Analytics. Meta-Orchestration .

Testing 300

Testing Machine Learning Consulting Data Quality 300

CIO Business Intelligence

NOVEMBER 29, 2022

Here, I’ll highlight the where and why of these important “data integration points” that are key determinants of success in an organization’s data and analytics strategy. It’s the foundational architecture and data integration capability for high-value data products. Data and cloud strategy must align.

Data Architecture 105

Data Architecture Data Integration IoT Strategy 105

Ontotext

JANUARY 10, 2024

And each of these gains requires data integration across business lines and divisions. Limiting growth by (data integration) complexity Most operational IT systems in an enterprise have been developed to serve a single business function and they use the simplest possible model for this. We call this the Bad Data Tax.

Metadata 72

Metadata Slice and Dice Data Integration Enterprise 72

IBM Big Data Hub

JUNE 12, 2023

For instance, the Job Recommendation function assists 180,000 employees in finding internal career opportunities; the Compensation Advisor, recommends Employee Salary Program increases to managers across the company; and the Performance to Skill indicator measures the scarcity of skills in the market. What is data quality?

Data Quality 66

Data Quality Data Governance People Analytics Data-driven 66

BI-Survey

AUGUST 21, 2020

Advanced analytics and new ways of working with data also create new requirements that surpass the traditional concepts. But what are the right measures to make the data warehouse and BI fit for the future? Can the basic nature of the data be proactively improved? Data must become a C-level priority.

Data Warehouse 98

Data Warehouse Data Lake Data Governance Data Architecture 98

Alation

MAY 16, 2023

Data Pipeline Use Cases Here are just a few examples of the goals you can achieve with a robust data pipeline: Data Prep for Visualization Data pipelines can facilitate easier data visualization by gathering and transforming the necessary data into a usable state.

Data Lake 69

Data Lake Data Governance Data Warehouse Data Processing 69

CIO Business Intelligence

MARCH 22, 2022

Then virtualize your data to allow business users to conduct aggregated searches and analyses using the business intelligence or data analytics tools of their choice. . Set up unified data governance rules and processes. With data integration comes a requirement for centralized, unified data governance and security.

Analytics 103

Analytics Key Performance Indicator Data Warehouse Data-driven 103

O'Reilly on Data

FEBRUARY 11, 2019

As companies ingest and use more data, there are many more users and consumers of that data within their organizations. Data lineage, data catalog, and data governance solutions can increase usage of data systems by enhancing trustworthiness of data. Data Platforms.

Big Data 207

Big Data Technology Machine Learning Deep Learning 207

CIO Business Intelligence

JANUARY 9, 2023

To fuel self-service analytics and provide the real-time information customers and internal stakeholders need to meet customers’ shipping requirements, the Richmond, VA-based company, which operates a fleet of more than 8,500 tractors and 34,000 trailers, has embarked on a data transformation journey to improve data integration and data management.

Data Strategy 110

Data Strategy Strategy Data Governance Marketing 110

Jet Global

MARCH 4, 2024

Data inconsistencies become commonplace, hindering visibility and inhibiting a holistic understanding of business operations. This lack of integration makes it difficult to track progress, measure performance, and identify potential issues. Data governance and compliance become a constant juggling act.

Management 52

Management Data Governance Reporting Software 52

DataKitchen

JANUARY 23, 2023

Data lineage can also be used for compliance, auditing, and data governance purposes. DataOps Observability Five on data lineage: Data lineage traces data’s origin, history, and movement through various processing, storage, and analysis stages. What is missing in data lineage?

Testing 130

Testing Data Governance Data Quality Data-driven 130

datapine

FEBRUARY 22, 2022

This includes defining the main stakeholders, assessing the situation, defining the goals, and finding the KPIs that will measure your efforts to achieve these goals. A planned BI strategy will point your business in the right direction to meet its goals by making strategic decisions based on real-time data.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

IBM Big Data Hub

OCTOBER 12, 2023

They’re built on machine learning algorithms that create outputs based on an organization’s data or other third-party big data sources. They can also spot and root out bias and drift proactively by monitoring, cataloging and governing their models. And that makes sense.

Cost-Benefit 79

Cost-Benefit Metadata Data Governance Modeling 79

FineReport

MAY 31, 2023

Return on assets measures the net profit generated per unit of asset, while return on equity (ROE) signifies the return on shareholders’ equity, indicating the efficiency of the company’s own capital. Ensuring seamless data integration and accuracy across these sources can be complex and time-consuming.

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

AWS Big Data

MARCH 26, 2024

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. Pillar 3: Analytics The analytics pillar defines capabilities that help you generate insights on top of your customer data.

Data Strategy 70

Data Strategy Strategy Data Warehouse Prescriptive Analytics 70

IBM Big Data Hub

OCTOBER 30, 2023

By combining IBM’s advanced data and AI capabilities powered by Watsonx platform with AWS’s unparalleled cloud services, the partnership aims to create an ecosystem where businesses can seamlessly integrate AI into their operations.

Insurance 81

Insurance Data Warehouse Data-driven Unstructured Data 81

Alation

MAY 16, 2023

Data Pipeline Use Cases Here are just a few examples of the goals you can achieve with a robust data pipeline: Data Prep for Visualization Data pipelines can facilitate easier data visualization by gathering and transforming the necessary data into a usable state.

Data Lake 40

Data Lake Data Governance Data Warehouse Data Processing 40

Alation

AUGUST 5, 2021

The abundance of data systems has also made the monitoring of complicated tasks even more challenging. Data governance practices Data governance is a data management system that adheres to an internal set of standards and policies for the collection, storage, and sharing of information.

Data Quality 52

Data Quality IT Data Governance Sales 52

AWS Big Data

JULY 19, 2023

Amazon Redshift is a fully managed and petabyte-scale cloud data warehouse that is used by tens of thousands of customers to process exabytes of data every day to power their analytics workload. You can structure your data, measure business processes, and get valuable insights quickly can be done by using a dimensional model.

Modeling 71

Modeling Sales Data Warehouse Snapshot 71

FineReport

APRIL 3, 2024

Integration capabilities are key for providing a holistic view and streamlining workflows. Security and Compliance: Data security is paramount. Choose a tool with robust security features to protect data integrity and comply with relevant regulations. Diverse visualization options enable effective communication.

Dashboards 52

Dashboards Visualization Metrics Interactive 52

IBM Big Data Hub

JANUARY 5, 2023

Both approaches were typically monolithic and centralized architectures organized around mechanical functions of data ingestion, processing, cleansing, aggregation, and serving. Meaning, data architecture is a foundational element of your business strategy for higher data quality. Creating a data architecture roadmap.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

CIO Business Intelligence

JANUARY 24, 2024

Ensures all automated processes adhere to regulatory standards and maintain data integrity and security. CyberSecurity Tools, Encryption, User Access Management Presentation Layer Provides an interface for human interaction, displaying processed data and insights in an accessible format.

IoT 105

IoT Machine Learning Optimization Internet of Things 105

Cloudera

MAY 9, 2019

The number one challenge that enterprises struggle with their IoT implementation is not being able to measure if they are successful or not with it. Data readiness – These set of metrics help you measure if your organization is geared up to handle the sheer volume, variety and velocity of IoT data.

IoT 54

IoT Modeling Metrics Measurement 54

FineReport

APRIL 9, 2024

Comparing Leading BI Tools Key Features and Capabilities When comparing leading business intelligence software tools and data analysis platforms , it is essential to evaluate a range of key features and capabilities that contribute to their effectiveness in enabling informed decision-making and data analysis.

Business Intelligence 52

Business Intelligence Software Data-driven Predictive Modeling 52