Smarten

JANUARY 30, 2024

The right self-serve data prep solution can provide easy-to-use yet sophisticated data prep tools that are suitable for your business users, and enable data preparation techniques like: Connect and Mash Up Auto Suggesting Relationships JOINS and Types Sampling and Outliers Exploration, Cleaning, Shaping Reducing and Combining Data Insights (Data Quality (..)

Analytics 67

Analytics Data Quality Visualization Metadata 67

DataKitchen

AUGUST 8, 2023

On 20 July 2023, Gartner released the article “ Innovation Insight: Data Observability Enables Proactive Data Quality ” by Melody Chien. It alerts data and analytics leaders to issues with their data before they multiply. It alerts data and analytics leaders to issues with their data before they multiply.

Data Quality 130

Data Quality Testing Snapshot Reporting 130

Octopai

OCTOBER 26, 2022

DataOps is an approach to best practices for data management that increases the quantity of data analytics products a data team can develop and deploy in a given time while drastically improving the level of data quality. Automated workflows for data product creation, testing and deployment.

Data Quality 52

Data Quality Data Analytics Analytics Manufacturing 52

CIO Business Intelligence

MARCH 24, 2023

The Business Application Research Center (BARC) warns that data governance is a highly complex, ongoing program, not a “big bang initiative,” and it runs the risk of participants losing trust and interest over time. The program must introduce and support standardization of enterprise data.

Data Governance 142

Data Governance Management Metadata Data Quality 142

AWS Big Data

MARCH 26, 2024

Without C360, businesses face missed opportunities, inaccurate reports, and disjointed customer experiences, leading to customer churn. AWS provides different services for building data ingestion pipelines: AWS Glue is a serverless data integration service that ingests data in batches from on-premises databases and data stores in the cloud.

Data Strategy 70

Data Strategy Strategy Data Warehouse Prescriptive Analytics 70

Ontotext

NOVEMBER 18, 2021

And all of them are asking hard questions: “Can you integrate my data, with my particular format?”, “How well can you scale?”, “How many visualizations do you offer?”. Nowadays, data analytics doesn’t exist on its own. You have to take care of data extraction, transformation and loading, and of visualization.

Visualization 98

Visualization Reporting Metadata Enterprise 98

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 Data Governance Key Performance Indicator Data Quality 111

erwin

FEBRUARY 28, 2024

While the essence of success in data governance is people and not technology, having the right tools at your fingertips is crucial. Technology is an enabler, and for data governance this is essentially having an excellent metadata management tool. Next to data governance, data architecture is really embedded in our DNA.

Metadata 52

Metadata Data Governance Data Quality Technology 52

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. Nine Steps to Data Modeling.

Modeling 98

Modeling Metadata Data Governance Visualization 98

BI-Survey

FEBRUARY 6, 2020

Modernizing and optimizing enterprise reporting – or classical BI – has not been such a priority for many of today’s organizations, even though it constitutes the backbone of information supply for decision support. Technological innovations and their increasing proliferation are shaping enterprise reporting and BI.

Reporting 59

Reporting Optimization Enterprise Data Quality 59

Cloudera

APRIL 1, 2024

This recognition is a testament to our vision and ability as a strategic partner to deliver an open and interoperable Cloud data platform, with the flexibility to use the best fit data services and low code, no code Generative AI infused practitioner tools.

Unstructured Data 104

Unstructured Data Cost-Benefit Metadata Machine Learning 104

erwin

DECEMBER 3, 2020

Being able to integrate all data touchpoints, including erwin DM for data modeling, Denodo for data visualization, and Jira for ticketing, has been key. Using erwin DI, customers are powering comprehensive data governance initiatives, cloud migration and other massive digital transformation projects.

Metadata 141

Metadata Data Governance Data-driven Digital Transformation 141

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

AWS Big Data

DECEMBER 18, 2023

AWS Step Functions is a fully managed visual workflow service that enables you to build complex data processing pipelines involving a diverse set of extract, transform, and load (ETL) technologies such as AWS Glue , Amazon EMR , and Amazon Redshift. There are multiple tables related to customers and order data in the RDS database.

Metadata 123

Metadata Visualization Data Lake Data-driven 123

Ontotext

MAY 2, 2024

These models are as important to companies as their frontline products and determine how data is managed, consumed, combined, joined, and analyzed. Data-centric approach In the data-centric approach, metadata serves as a layer of interoperability between the data sources.

Metadata 52

Metadata Data Lake Data-driven Enterprise 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

CIO Business Intelligence

DECEMBER 21, 2022

BI software helps companies do just that by shepherding the right data into analytical reports and visualizations so that users can make informed decisions. Determining which BI delivery method fits best There are many traditional IT-managed ways to deliver reports and insights from data.

IT 130

IT Business Intelligence Sales Key Performance Indicator 130

Octopai

JANUARY 21, 2020

How much time has your BI team wasted on finding data and creating metadata management reports? BI groups spend more than 50% of their time and effort manually searching for metadata. In fact, BI projects used to take many months to complete and require huge numbers of IT professionals to extract data.

OLAP 56

OLAP Metadata Online Analytical Processing Data Quality 56

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

CIO Business Intelligence

NOVEMBER 22, 2022

Data fabric is an architecture that enables the end-to-end integration of various data pipelines and cloud environments through the use of intelligent and automated systems. The fabric, especially at the active metadata level, is important, Saibene notes.

Data Strategy 145

Data Strategy Strategy Enterprise Consulting 145

Octopai

MAY 31, 2022

A data lineage tool gives you visibility and transparency into your data: where your numbers came from, where they ended up, and what happened to them along their journey from source systems all the way to BI reporting tools. Bonus tool: active metadata management. when compared to a DIY version.

Management 52

Management Metadata Business Intelligence ROI 52

AWS Big Data

JUNE 14, 2023

We’ve made a big impact with QuickSight because it doesn’t require in-depth knowledge about data visualizations to build dashboards and provide insights, empowering our users to build what they need. This empowers EMs to avoid building disparate local reporting that creates logic inconsistencies and data security issues.

Dashboards 78

Dashboards KPI Scorecard Metadata 78

datapine

JANUARY 31, 2022

BI software uses algorithms to extract actionable insights from a company’s data and guide its strategic decisions. BI users analyze and present data in the form of dashboards and various types of reports to visualize complex information in an easier, more approachable way. 6) Smart and faster reporting.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

Octopai

APRIL 5, 2020

When reliant on manual procedures, sometimes reports or procedures just can’t get done at all due to the length of time required, or otherwise, they are prone to human error, time-consuming, and cumbersome. This is when automated data lineage saves the day, literally. Stop drowning in data prep. 80% faster data lineage?!

Metadata 52

Metadata Data Quality Reporting Management 52

DataKitchen

JANUARY 23, 2023

It allows organizations to see how data is being used, where it is coming from, its quality, and how it is being transformed. DataOps Observability includes monitoring and testing the data pipeline, data quality, data testing, and alerting. Data lineage is static and often lags by weeks or months.

Testing 130

Testing Data Governance Data Quality Data-driven 130

Alation

DECEMBER 21, 2022

Master Data Management (MDM) and data catalog growth are accelerating because organizations must integrate more systems, comply with privacy regulations, and address data quality concerns. What Is Master Data Management (MDM)? Data Catalog and Master Data Management. Assess Data Quality.

Management 52

Management Data Quality Metadata Testing 52

Octopai

FEBRUARY 9, 2023

It’s not easy to keep up with data and metadata on the move. A comprehensive data lineage tool is the secret weapon of successful data governance managers and data stewards. Let’s take a look at four major areas where data lineage will improve your performance a hundredfold if you are in data governance.

Data Governance 52

Data Governance Metadata Data Quality Management 52

AWS Big Data

MARCH 7, 2023

Sources Data can be loaded from multiple sources, such as systems of record, data generated from applications, operational data stores, enterprise-wide reference data and metadata, data from vendors and partners, machine-generated data, social sources, and web sources.

Analytics 74

Analytics Data Warehouse Data Lake Metadata 74

Octopai

JANUARY 19, 2021

With Octopai’s support and analysis of Azure Data Factory, enterprises can now view complete end-to-end data lineage from Azure Data Factory all the way through to reporting for the first time ever.

Metadata 52

Metadata ROI Optimization Data Quality 52

IBM Big Data Hub

MAY 9, 2022

Data privacy laws such as the GDPR in the EU, CCPA in California and PIPEDA in Canada have been enacted at the same time businesses are revitalizing efforts to establish data quality, not just data volume. Poor data quality costs organizations an average of $12.9 million each year [1] and $1.2 28, 2021. [2].

Management 56

Management Data Quality Metadata Data Integration 56

Ontotext

MAY 16, 2024

Industry analyst reports place contextualized information and graph technologies at the center of their impact radar for emerging technologies. Acknowledging the significance of how these critical enablers define, contextualize, and constrain data for consistency and trust, is all part of the maturity process for today’s enterprise.

Enterprise 52

Enterprise Data-driven Cost-Benefit Digital Transformation 52

Octopai

JUNE 24, 2019

This maintains a high priority in your data governance strategy. As such, your chosen tool must provide data quality management, perform data movement, track modifications of metadata objects, support cascade changes, expose metadata, and be capable of printing visual representations of data lineage.

Data Governance 42

Data Governance Metadata Unstructured Data Software 42

Jet Global

MARCH 14, 2024

Jet’s interface lets you handle data administration easily, without advanced coding skills. You don’t need technical skills to manage complex data workflows in the Fabric environment. Code Portability and Flexibility Jet’s architecture ensures that your data solutions aren’t restricted to OneLake.

Analytics 52

Analytics Management Reporting Enterprise 52

IBM Big Data Hub

JULY 13, 2023

When we talk about data integrity, we’re referring to the overarching completeness, accuracy, consistency, accessibility, and security of an organization’s data. Together, these factors determine the reliability of the organization’s data. Data quality Data quality is essentially the measure of data integrity.

Data Quality 66

Data Quality Data Integration Metadata Cost-Benefit 66

Octopai

JANUARY 31, 2021

The particular episode we recommend looks at how WeWork struggled with understanding their data lineage so they created a metadata repository to increase visibility. Agile Data. Another podcast we think is worth a listen is Agile Data. TDWI – Philip Russom.

Data Governance 57

Data Governance Data Processing Data Quality Metadata 57

BizAcuity

MARCH 29, 2019

Data lakes are centralized repositories that can store all structured and unstructured data at any desired scale. The power of the data lake lies in the fact that it often is a cost-effective way to store data. Numbers are only good if the data quality is good.

Data Lake 102

Data Lake Unstructured Data Cost-Benefit Data Quality 102

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