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 quality.

Data-driven 58

Data-driven Enterprise Data Governance Data Lake 58

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

IBM Big Data Hub

DECEMBER 16, 2022

For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance. It uses metadata and data management tools to organize all data assets within your organization. Ensuring data quality is made easier as a result.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

Jet Global

FEBRUARY 5, 2019

states that about 40 percent of enterprise data is either inaccurate, incomplete, or unavailable. This poor data quality translates into an average of $15 million per year in a ripple effect of financial loss, missed opportunities, and high-risk decision making. Because bad data is the reason behind poor analytics. .

Data Quality 69

Data Quality Data Warehouse Business Intelligence Data Governance 69

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

AWS Big Data

JANUARY 31, 2023

Data governance is the collection of policies, processes, and systems that organizations use to ensure the quality and appropriate handling of their data throughout its lifecycle for the purpose of generating business value.

Data Lake 78

Data Lake Data Governance Data Architecture Machine Learning 78

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

Cloudera

SEPTEMBER 15, 2022

The consumption of the data should be supported through an elastic delivery layer that aligns with demand, but also provides the flexibility to present the data in a physical format that aligns with the analytic application, ranging from the more traditional data warehouse view to a graph view in support of relationship analysis.

Data Lake 83

Data Lake Data Architecture Data-driven Data Warehouse 83

Alation

APRIL 27, 2023

Article reposted with permission from Eckerson ABSTRACT: Data mesh is giving many of us from the data warehouse generation a serious case of agita. But, my fellow old-school data tamers, it’s going to be ok. It’s a subject that’s giving many of us from the data warehouse generation a serious case of agita.

Data Warehouse 52

Data Warehouse Risk Data-driven Metadata 52

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. But today, there is a magic quadrant for cloud databases and warehouses comprising more than 20 vendors. What do you migrate, how, and when?

Data Warehouse 69

Data Warehouse Cost-Benefit Data Governance Data-driven 69

Alation

APRIL 27, 2023

Article reposted with permission from Eckerson ABSTRACT: Data mesh is giving many of us from the data warehouse generation a serious case of agita. But, my fellow old-school data tamers, it’s going to be ok. It’s a subject that’s giving many of us from the data warehouse generation a serious case of agita.

Data Warehouse 40

Data Warehouse Risk Data-driven Metadata 40

Jet Global

JULY 2, 2019

The sheer scale of data being captured by the modern enterprise has necessitated a monumental shift in how that data is stored. From the humble database through to data warehouses , data stores have grown both in scale and complexity to keep pace with the businesses they serve, and the data analysis now required to remain competitive.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

Ontotext

MARCH 8, 2023

Use Case #4: Financial Risk Detection and Prediction The financial industry is made up of a network of markets and transactions. A risk issue in one financial institution could result in a domino effect for many. Which financial institutions have filed similar risk compliance issues?

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

Ontotext

MARCH 18, 2020

The many data warehouse systems designed in the last 30 years present significant difficulties in that respect. When designing a system’s architecture, it’s impossible to know from the start all the ways data will be used. The third challenge is how to combine data management with analytics.

Enterprise 59

Enterprise B2B Unstructured Data Machine Learning 59

FineReport

MAY 31, 2023

Finance and accounting teams often deal with data residing in multiple systems, such as accounting software, ERP systems, spreadsheets, and data warehouses. Ensuring seamless data integration and accuracy across these sources can be complex and time-consuming.

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

Alation

FEBRUARY 13, 2020

Important evaluation features include capabilities to preview a dataset, see all associated metadata, see user ratings, read user reviews and curator annotations, and view data quality information. Benefits of a Data Catalog. Improved data efficiency. Improved data context. Reduced risk of error.

Metadata 64

Metadata Data Lake Recreation/Entertainment Big Data 64

Domino Data Lab

JULY 22, 2019

data science’s emergence as an interdisciplinary field – from industry, not academia. why data governance, in the context of machine learning is no longer a “dry topic” and how the WSJ’s “global reckoning on data governance” is potentially connected to “premiums on leveraging data science teams for novel business cases”.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

BI-Survey

FEBRUARY 17, 2020

From operational systems to support “smart processes”, to the data warehouse for enterprise management, to exploring new use cases through advanced analytics : all of these environments incorporate disparate systems, each containing data fragments optimized for their own specific task. .

Data Governance 89

Data Governance Data Warehouse Data Quality Data Strategy 89

erwin

FEBRUARY 19, 2021

A strong data management strategy and supporting technology enables the data quality the business requires, including data cataloging (integration of data sets from various sources), mapping, versioning, business rules and glossaries maintenance and metadata management (associations and lineage). Harvest data.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

BizAcuity

APRIL 14, 2022

Big Data technology in today’s world. Did you know that the big data and business analytics market is valued at $198.08 Or that the US economy loses up to $3 trillion per year due to poor data quality? quintillion bytes of data which means an average person generates over 1.5 megabytes of data every second?

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

AWS Big Data

MARCH 26, 2024

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data.

Data Strategy 66

Data Strategy Strategy Data Warehouse Prescriptive Analytics 66

Alation

OCTOBER 21, 2021

But, on the back end, data lakes give businesses a common repository to collect and store data, streamlined usage from a single source, and access to the raw data necessary for today’s advanced analytics and artificial intelligence (AI) needs. Irrelevant data. Ungoverned data. So what is a Data Lakehouse?

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

Jet Global

JANUARY 17, 2019

Here are 5 ways that MDM can help you better organize your Dynamics ERP data for BI and analytics: Simplifies Data Structure. With all of your data mapping to your master data, you get a more clear and controlled view of your operations and how you are performing. Develops Data Governance. Download Now.

Business Intelligence 75

Business Intelligence Management Data Warehouse Data Governance 75

IBM Big Data Hub

OCTOBER 12, 2023

Accounting for the complexities of the AI lifecycle Unfortunately, typical data storage and data governance tools fall short in the AI arena when it comes to helping an organization perform the tasks that underline efficient and responsible AI lifecycle management. And that makes sense.

Cost-Benefit 83

Cost-Benefit Metadata Data Governance Modeling 83

Octopai

DECEMBER 12, 2021

How many different data systems do you have in your BI environment? The average data intelligence stack is comprised of the following components – ETL, data warehouse/database, analysis, and reporting – for each of which you may use one or multiple systems. Data catalogs. Metadata harvesting.

Metadata 93

Metadata Management Data Quality Data Governance 93

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 84

Cost-Benefit Metadata Optimization Management 84

datapine

FEBRUARY 22, 2022

Improved risk management: Another great benefit from implementing a strategy for BI is risk management. This should also include creating a plan for data storage services. Are the data sources going to remain disparate? Or does building a data warehouse make sense for your organization? Define a budget.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

Alation

AUGUST 17, 2021

The Alation Data Catalog is built as a platform, unifying disparate data into a singular view. The Alation Data Catalog enables you to leverage the Data Cloud to boost analyst productivity, accelerate migration, and minimize risk through active data governance. Empower Anyone to Find Trusted Data.

Data Governance 52

Data Governance Cost-Benefit Enterprise Metadata 52

erwin

JANUARY 10, 2024

The result is an improvement in quality and availability of data such that you can monetize it. Your goal should be enterprise data management and an analytics function that pays for itself, like a self-funding data warehouse, data lake or data mesh. What is data monetization?

Measurement 59

Measurement Cost-Benefit Data Governance Management 59

AWS Big Data

FEBRUARY 27, 2024

The following are the key components of the Bluestone Data Platform: Data mesh architecture – Bluestone adopted a data mesh architecture, a paradigm that distributes data ownership across different business units. This enables data-driven decision-making across the organization.

Data-driven 90

Data-driven Data Lake Data Quality Data Governance 90

IBM Big Data Hub

AUGUST 4, 2023

Data democratization instead refers to the simplification of all processes related to data, from storage architecture to data management to data security. It also requires an organization-wide data governance approach, from adopting new types of employee training to creating new policies for data storage.

Data Architecture 64

Data Architecture Data Lake Machine Learning Data Governance 64

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

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. Outsourcing these data management efforts to professional services firms only delays schedules and increases costs. With automation, data quality is systemically assured.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

Alation

AUGUST 26, 2021

It asks much larger questions, which flesh out an organization’s relationship with data: Why do we have data? Why keep data at all? Answering these questions can improve operational efficiencies and inform a number of data intelligence use cases, which include data governance, self-service analytics, and more.

Metadata 64

Metadata Data Governance Dashboards Software 64

Alation

APRIL 19, 2022

Further, data modernization reduces data security and privacy compliance risks. Its process includes identifying sensitive information so you can limit users’ access to data precisely and efficiently. In that sense, data modernization is synonymous with cloud migration. Use of Reliable Databases.

Cost-Benefit 52

Cost-Benefit Data Governance Manufacturing Data Architecture 52

Andrew White

JANUARY 11, 2021

But we also know not all data is equal, and not all data is equally valuable. Some data is more a risk than valuable. Additionally, the value of data may change, and our own personal judgement of the the same data and its value may differ. Governance. Link Data to Business Outcomes.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

Andrew White

MARCH 22, 2019

This ties into the failure of data governance and MDM (see first item in this list). A data hub strategy should be economical, not perfected; and a data hub does not collect data like a data warehouses or data lake does – they are very different things. Strategy is Learning By Doing.

Analytics 68

Analytics Metadata Data Governance Management 68