IoT Data Governance: Taming the Deluge in Connected Environments
Dataversity
JANUARY 8, 2024
However, the sheer volume and complexity of data generated by an ever-growing network of connected devices presents unprecedented challenges.
Strategies for Reducing Resistance and Encouraging Adoption
Analysts Corner
OCTOBER 26, 2024
Source: Mirko Peters with MidJourney and Canva Have you ever walked into a meeting brimming with excitement about a new data project, only to be met with blank stares and crossed arms? I remember my first presentation on a data governance initiative; I was full of hope, but the room felt as cold as an icebox.
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Data Sips: Interview with Seth Maislin
Dataversity
FEBRUARY 21, 2025
Data Sips is a new video miniseries presented by Ippon Technologies and DATAVERSITY that showcases quick conversations with industry experts from last months Data Governance & Information Quality (DGIQ) Conference in Washington, D.C.
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Data Sips: Interview with InfoAdvisors’ Karen Lopez
Dataversity
JANUARY 17, 2025
Data Sips is a new video miniseries presented by Ippon Technologies and DATAVERSITY that showcases quick conversations with industry experts from last months Data Governance & Information Quality (DGIQ) Conference in Washington, D.C.
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A Practical Guide to Business Intelligence Governance
Speaker: Marius Moscovici, CEO Metric Insights & Mike Smitheman, VP Metric Insights
While the proper governance of data is clearly critical to the success of any business intelligence organization, focusing on data governance alone is a huge mistake. Organizations continually fail to generate ROI on their governance initiatives because they are too narrow in scope.
Data Sips: Interview with Tom Redman
Dataversity
JANUARY 31, 2025
Data Sips is a new video miniseries presented by Ippon Technologies and DATAVERSITY that showcases quick conversations with industry experts from last months Data Governance & Information Quality (DGIQ) Conference in Washington, D.C.
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From Challenges to Triumph: WaterWipes’ Data Management Revolution with Maextro
Timo Elliott
DECEMBER 10, 2024
The session by Liz Cotter , Data Manager for Water Wipes, and Richard Henry , Commercial Director of BluestoneX Consulting, was called From Challenges to Triumph: WaterWipes’ Data Management Revolution with Maextro. Impact of Errors : Erroneous data posed immediate risks to operations and long-term damage to customer trust.
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Building a Grassroots Data Management and Data Governance Program
Dataversity
NOVEMBER 1, 2021
Many in enterprise Data Management know the challenges that rapid business growth can present. Whether through acquisition or organic growth, the amount of enterprise data coming into the organization can feel exponential as the business hires more people, opens new locations, and serves new customers. The enterprise […].
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AstraZeneca’s Axial Transformation: A Digital Backbone for Innovation
Timo Elliott
DECEMBER 6, 2024
Russell Smith, Vice President ERP Transformation and Ade Welsh, Senior Director, Head Of Solution Design & Delivery gave the keynote presentation at the Birmingham event. Here are the key lessons learned so far: Russell Smith and Ade Walsh of AstraZeneca presenting at UKISUG Connect 2024 1.
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Why Data Quality and Data Governance are Important to Achieve Compliance
Analysts Corner
JANUARY 12, 2023
In this article, we present a brief overview of compliance and regulations, discuss the cost of non-compliance and some related statistics, and the role data quality and data governance play in achieving compliance. The average cost of a data breach among organizations surveyed reached $4.24
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What is the Future of Business Intelligence in the Coming Year?
Smart Data Collective
NOVEMBER 24, 2020
Business intelligence software will be more geared towards working with Big Data. Data Governance. One issue that many people don’t understand is data governance. It is evident that challenges of data handling will be present in the future too. Access to Essential Information. Increase in ROI.
Data Sips: Interview with Mark Cooper
Dataversity
FEBRUARY 14, 2025
Data Sips is a new video miniseries presented by Ippon Technologies and DATAVERSITY that showcases quick conversations with industry experts from last months Data Governance & Information Quality (DGIQ) Conference in Washington, D.C.
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6 Big Data Mistakes You Must Avoid At All Costs
Smart Data Collective
FEBRUARY 23, 2021
Not Having a Data Architecture Plan. Data quality matters, but along with that, even its structure matters. When you’re dealing with big data, it’s essential that you manage it well. Without a data governance framework in place, you won’t be able to find and retrieve the required data with ease. What’s more?
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Don’t Create a Data Governance Tug of War between Financial Pros and IT Staff
ElegantJ BI
AUGUST 10, 2016
But, in an age of user and data breaches, the IT team may be hesitant to allow meaningful, flexible access to critical business intelligence. The team can also monitor data warehouses, legacy systems and best-of-breed solutions and identify redundant data, performance issues, data parameters, or data integrity issues.
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Don’t Create a Data Governance Tug of War between Financial Pros and IT Staff
ElegantJ BI
AUGUST 10, 2016
But, in an age of user and data breaches, the IT team may be hesitant to allow meaningful, flexible access to critical business intelligence. The team can also monitor data warehouses, legacy systems and best-of-breed solutions and identify redundant data, performance issues, data parameters, or data integrity issues.
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Don’t Create a Data Governance Tug of War between Financial Pros and IT Staff
ElegantJ BI
AUGUST 10, 2016
But, in an age of user and data breaches, the IT team may be hesitant to allow meaningful, flexible access to critical business intelligence. In order to protect the enterprise, and its interests, the IT team must: Ensure compliance with government and industry regulation and internal data governance policies.
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How to: Focus on three areas for a holistic data governance approach for self-service analytics
Tableau
SEPTEMBER 23, 2021
If we asked you, “What does your organization need to help more employees be data-driven?” where would “better data governance” land on your list? We’re all trying to use more data to make decisions, but constantly face roadblocks and trust issues related to data governance. . A data governance framework.
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How to: Focus on three areas for a holistic data governance approach for self-service analytics
Tableau
SEPTEMBER 23, 2021
If we asked you, “What does your organization need to help more employees be data-driven?” where would “better data governance” land on your list? We’re all trying to use more data to make decisions, but constantly face roadblocks and trust issues related to data governance. . A data governance framework.
Understanding the Importance of Data Resilience
Dataversity
SEPTEMBER 11, 2024
In recent years, the frequency and sophistication of cyberattacks have surged, presenting a formidable challenge to organizations worldwide. My company’s 2024 Data Protection Trends report revealed that 75% of organizations experience […] The post Understanding the Importance of Data Resilience appeared first on DATAVERSITY.
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Key Highlights from Data Intelligence Day 2025 Amsterdam by Databricks
Analysts Corner
MARCH 30, 2025
This success story was presented by Dmitry Ratushnyak, Global Lead of Data Engineering. First, since Unileverthe parent company of Lipton before it was spun offhad already been using Databricks, there was no need to migrate to another data lakehouse provider.
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How Data Cleansing Can Make or Break Your Business Analytics
Smart Data Collective
DECEMBER 21, 2022
This can be done using a data cleansing solution like WinPure that lets you identify the noise affecting your data. Second, standardize the way you are presenting the data so that each field is formatted correctly for analysis. You can identify fields with odd characters, with typos, errors, and much more.
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(Most) Self-Serve BI Tools will Create Data Anarchy– Myth#2
ElegantJ BI
DECEMBER 15, 2015
Debunking Common Business Intelligence Myths Myth #2 – True Self-Serve BI Tools Will Compromise Data Governance Today’s business intelligence market offers many options! In this, the second of the article series, we delve into data governance and separate fact from fiction.
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(Most) Self-Serve BI Tools will Create Data Anarchy– Myth#2
ElegantJ BI
DECEMBER 15, 2015
Debunking Common Business Intelligence Myths Myth #2 – True Self-Serve BI Tools Will Compromise Data Governance Today’s business intelligence market offers many options! In this, the second of the article series, we delve into data governance and separate fact from fiction.
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(Most) Self-Serve BI Tools will Create Data Anarchy– Myth#2
ElegantJ BI
DECEMBER 15, 2015
Myth #2 – True Self-Serve BI Tools Will Compromise Data Governance. In this, the second of the article series, we delve into data governance and separate fact from fiction. In many BI implementation scenarios, accessibility, trust and usability of Business Intelligence (BI) solutions is hampered by Data Anarchy.
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26 Interesting Statistics around Big Data, Data Science, and Analytics Market, Jobs, and Salaries
Analysts Corner
DECEMBER 21, 2022
A lack of awareness has led to less competition in the data science field. In this article, we present some interesting statistics around the following, that should help you decide for yourself as to where you are headed for with job in data science : Big Data, Data Science, and Analytics Market; Data Scientist — Job and Salary.
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Building a Data Science career without coding
The BAWorld
JULY 22, 2024
Data Analyst Data Analyst’s primary task is to collect the data and analyze it for organizations to make informed decisions. You do not need to know programming for most of the Data Analysts jobs. Such visuals simplify complex data, aiding businesses and stakeholders to comprehend easily.
Through the Looking Glass: Data Stewards in the Realm of Gondor
The Data Administration Newsletter
MARCH 2, 2021
In this and future columns, I will look at data from diverse and even eccentric perspectives, presenting fresh and sometimes whimsical views of these much-discussed topics. Readers of TDAN.com may recall my previous articles where I explored data governance from the perspective of classical […].
Why Do You Need Self-Serve Data Preparation?
ElegantJ BI
MARCH 7, 2018
Self-Serve Data Preparation Takes the Headache Out of Data Analytics! Self-Serve Data Preparation (aka augmented data preparation) is all about efficiency and the presentation of sophisticated data preparation tools in an easy-to-use environment.
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Why Do You Need Self-Serve Data Preparation?
ElegantJ BI
MARCH 7, 2018
Self-Serve Data Preparation Takes the Headache Out of Data Analytics! Self-Serve Data Preparation (aka augmented data preparation) is all about efficiency and the presentation of sophisticated data preparation tools in an easy-to-use environment.
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Why Do You Need Self-Serve Data Preparation?
ElegantJ BI
MARCH 7, 2018
Self-Serve Data Preparation Takes the Headache Out of Data Analytics! Self-Serve Data Preparation (aka augmented data preparation) is all about efficiency and the presentation of sophisticated data preparation tools in an easy-to-use environment.
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Self-Service Data Prep: A Tool for Business Users
ElegantJ BI
SEPTEMBER 29, 2017
Users can clean, reduce and clarify data using sophisticated algorithms in an easy-to-use environment that is agile and provides accurate, dependable data governance to satisfy the IT team.
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Self-Service Data Prep: A Tool for Business Users
ElegantJ BI
SEPTEMBER 29, 2017
Users can clean, reduce and clarify data using sophisticated algorithms in an easy-to-use environment that is agile and provides accurate, dependable data governance to satisfy the IT team.
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Self-Service Data Prep: A Tool for Business Users
ElegantJ BI
SEPTEMBER 29, 2017
Users can clean, reduce and clarify data using sophisticated algorithms in an easy-to-use environment that is agile and provides accurate, dependable data governance to satisfy the IT team.
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Interesting statistics around big data, data analysis, and usage
Analysts Corner
FEBRUARY 5, 2023
An IBM study states 80% of data scientists utilize their time finding, organizing, and cleansing data (that is improving data quality), and only 20% on data analysis. It is not astonishing that a 2022 data quality survey discovered that poor data quality impacts 26% of their companies’ revenue.
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How Data Management and Big Data Analytics Speed Up Business Growth
BizAcuity
APRIL 14, 2022
Ensuring rich data quality, maximum security & governance, maintenance, efficiency in storage and analysis comes under the umbrella term of Data Management. With the amount of data being accumulated, it is easier when said. Challenges associated with Data Management and Optimizing Big Data.
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Succeed As a Business Analyst
Analysts Corner
NOVEMBER 24, 2022
Business Analysts- Key Skills Some of the most important skills and experience for a business analyst are (Pratt and White 2019): Oral and written communication skills, including presentation skills and documentation skills; Listening skills; Time management skills; Stakeholder management skills; Ability to run meetings/conduct workshops and interviews (..)
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Data Warehouse, Data Lake, Data Mart, Data Hub: A Definition of Terms!
ElegantJ BI
APRIL 28, 2021
A Data Warehouse is a structured environment that is comprised of one or more databases and organized in tiers. An interactive, front-end tier provides search results for reporting, analytics and data mining. A Data Lake stores data with no organization or hierarchy.
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Data Warehouse, Data Lake, Data Mart, Data Hub: A Definition of Terms!
ElegantJ BI
APRIL 28, 2021
A Data Warehouse is a structured environment that is comprised of one or more databases and organized in tiers. An interactive, front-end tier provides search results for reporting, analytics and data mining. A Data Lake stores data with no organization or hierarchy.
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Advanced Analytics: If You Don’t Know What You Need, How Can You Succeed?
ElegantJ BI
SEPTEMBER 15, 2017
Your organization can enjoy an interactive view and clean, clear data so that it is easier to use and interpret to provide data quality and clear watermarks to identify the source of data. If you select the right solution, you can ensure data and personal security and provide appropriate access at all levels of the organization.
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Advanced Analytics: If You Don’t Know What You Need, How Can You Succeed?
ElegantJ BI
SEPTEMBER 15, 2017
Your organization can enjoy an interactive view and clean, clear data so that it is easier to use and interpret to provide data quality and clear watermarks to identify the source of data. If you select the right solution, you can ensure data and personal security and provide appropriate access at all levels of the organization.
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Advanced Analytics: If You Don’t Know What You Need, How Can You Succeed?
ElegantJ BI
SEPTEMBER 15, 2017
Your organization can enjoy an interactive view and clean, clear data so that it is easier to use and interpret to provide data quality and clear watermarks to identify the source of data. Data Governance and Self-Serve Analytics Go Hand in Hand.
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Factors and Considerations Involved in Choosing a Data Management Solution!
ElegantJ BI
SEPTEMBER 30, 2021
In the first article in our two-part series, entitled, ‘ Data Warehouse, Data Lake, Data Mart, Data Hub: A Definition of Terms ’, we defined the terms and differences in the market so that businesses can better understand the possibilities of Data Warehouses, Data Marts, Data Lakes and Data Hubs.
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Factors and Considerations Involved in Choosing a Data Management Solution!
ElegantJ BI
SEPTEMBER 30, 2021
In the first article in our two-part series, entitled, ‘ Data Warehouse, Data Lake, Data Mart, Data Hub: A Definition of Terms ’, we defined the terms and differences in the market so that businesses can better understand the possibilities of Data Warehouses, Data Marts, Data Lakes and Data Hubs.
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Factors and Considerations Involved in Choosing a Data Management Solution!
ElegantJ BI
SEPTEMBER 30, 2021
In the first article in our two-part series, entitled, ‘ Data Warehouse, Data Lake, Data Mart, Data Hub: A Definition of Terms ’, we defined the terms and differences in the market so that businesses can better understand the possibilities of Data Warehouses, Data Marts, Data Lakes and Data Hubs.
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