AWS Big Data

JUNE 6, 2023

Alerts and notifications play a crucial role in maintaining data quality because they facilitate prompt and efficient responses to any data quality issues that may arise within a dataset. This proactive approach helps mitigate the risk of making decisions based on inaccurate information.

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IBM Big Data Hub

FEBRUARY 28, 2024

Sourcing teams are automating processes like data analysis as well as supplier relationship management and transaction management. This helps reduce errors to improve data quality and response times to questions, which improves customer and supplier satisfaction. How is sourcing strategy different than procurement strategy?

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TDAN

MAY 4, 2022

Getting to great data quality need not be a blood sport! This article aims to provide some practical insights gained from enterprise master data quality projects undertaken within the past […].

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Smart Data Collective

APRIL 20, 2022

Companies that utilize data analytics to make the most of their business model will have an easier time succeeding with Amazon. One of the best ways to create a profitable business model with Amazon involves using data analytics to optimize your PPC marketing strategy. However, it is important to make sure the data is reliable.

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TDAN

MARCH 15, 2022

1 In this article, I will apply it to the topic of data quality. I will do so by comparing two butterflies, each that represent a common use of data quality: firstly and most commonly in situ for existing systems, and secondly for use […]. We know the phrase, “Beauty is in the eye of the beholder.”1

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CIO Business Intelligence

NOVEMBER 22, 2022

Every enterprise needs a data strategy that clearly defines the technologies, processes, people, and rules needed to safely and securely manage its information assets and practices. Here’s a quick rundown of seven major trends that will likely reshape your organization’s current data strategy in the days and months ahead.

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Smart Data Collective

SEPTEMBER 29, 2022

A growing number of companies have leveraged big data to cut costs, improve customer engagement, have better compliance rates and earn solid brand reputations. The benefits of big data cannot be overstated. One study by Think With Google shows that marketing leaders are 130% as likely to have a documented data strategy.

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TDAN

OCTOBER 18, 2022

Last week, we presented a webinar in our Data Governance — Best Practices series on data quality. Obviously, we’re a […].

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CIO Business Intelligence

JUNE 23, 2023

According to the MIT Technology Review Insights Survey, an enterprise data strategy supports vital business objectives including expanding sales, improving operational efficiency, and reducing time to market. The problem is today, just 13% of organizations excel at delivering on their data strategy.

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IBM Big Data Hub

JUNE 12, 2023

People analytics is at the center of human resources (HR) strategy and planning. Companies rely heavily on data and analytics to find and retain talent, drive engagement, improve productivity and more across enterprise talent management. According to a Gartner report , poor data quality costs organizations an average of USD 12.9

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CIO Business Intelligence

MARCH 4, 2024

The data mesh debate This is not to say that there is a consensus that data mesh is a universal solution. Stakeholders are currently waging an open debate across the industry of centralization versus federated data strategies. To learn more, visit us here.

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IBM Big Data Hub

DECEMBER 20, 2023

Without an AI strategy, organizations risk missing out on the benefits AI can offer. An AI strategy helps organizations address the complex challenges associated with AI implementation and define its objectives. What is an AI strategy? A successful AI strategy should act as a roadmap for this plan.

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Strategy Business Objectives Cost-Benefit Consulting 76

CIO Business Intelligence

JUNE 9, 2023

Such is the case with a data management strategy. That gap is becoming increasingly apparent because of artificial intelligence’s (AI) dependence on effective data management. A few years ago, Gartner found that “organizations estimate the average cost of poor data quality at $12.8 The second best time is now.”

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IBM Big Data Hub

AUGUST 2, 2023

People analytics is at the center of Human Resources (HR) strategy. Companies rely heavily on data and analytics to find and retain talent, drive engagement, and improve productivity. However, analytics are only as good as the quality of the data, which aims to be error-free, trustworthy, and transparent.

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TDAN

APRIL 5, 2022

Regardless of how accurate a data system is, it yields poor results if the quality of data is bad. As part of their data strategy, a number of companies have begun to deploy machine learning solutions. In a recent study, AI and machine learning were named as the top data priorities for 2021, by 61% […].

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TDAN

DECEMBER 2, 2020

Ensuring data quality is an important aspect of data management and these days, DBAs are increasingly being called upon to deal with the quality of the data in their database systems more than ever before. The importance of quality data cannot be overstated.

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Alation

OCTOBER 5, 2021

Answers will differ widely depending upon a business’ industry and strategy for growth. The first step towards a successful data governance strategy is setting appropriate goals and milestones. Yet, so many companies today are still failing miserably in implementing data strategy and governance protocols.

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IBM Big Data Hub

NOVEMBER 4, 2022

Data is the new oil and organizations of all stripes are tapping this resource to fuel growth. However, data quality and consistency are one of the top barriers faced by organizations in their quest to become more data-driven. Unlock quality data with IBM. and its leading data observability offerings.

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Ontotext

MARCH 20, 2024

Traditional data integration methods struggle to bridge these gaps, hampered by high costs, data quality concerns, and inconsistencies. Studies reveal that businesses lose significant time and opportunities due to missing integrations and poor data quality and accessibility.

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TDAN

AUGUST 31, 2021

Data is everywhere! But can you find the data you need? What can be done to ensure the quality of the data? How can you show the value of investing in data? Can you trust it when you get it? These are not new questions, but many people still do not know how to practically […].

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Anmut

JULY 12, 2021

Data without context is just meaningless noise, and any effort to improve or extract value from your data without considering the larger business context is doomed to fall short.? Unfortunately, traditional approaches to data remediation often focus on technical data quality in isolation from the broader data and business ecosystem.

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TDAN

JUNE 1, 2021

“Quality is never an accident. ” John Ruskin, prominent Victorian era social thinker Data-driven decision-making is fast becoming a critical business strategy for organizations in every sector. However, if the data used to make these decisions is not high-quality, it can’t be trusted.

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Alation

MARCH 14, 2023

Data gathering and use pervades almost every business function these days — and it’s widely acknowledged that businesses with a clear strategy around data are best placed to succeed in competitive, challenging markets such as defence. What is a data strategy? Why is a data strategy important?

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TDAN

FEBRUARY 21, 2024

Many Data Governance or Data Quality programs focus on “critical data elements,” but what are they and what are some key features to document for them? A critical data element is any data element in your organization that has a high impact on your organization’s ability to execute its business strategy.

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IBM Big Data Hub

APRIL 10, 2023

Data fabric can help model, integrate and query data sources, build data pipelines, integrate data in near real-time, and run AI-driven applications. This data foundation is crucial for truly effective ESG strategies that can help boost business value and manage evolving sustainability regulations around the globe.

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Jim Harris

DECEMBER 24, 2015

Have you ever experienced that sinking feeling, where you sense if you don’t find data quality, then data quality will find you? These discussions are a critical prerequisite for determining data usage, standards, and the business relevant metrics for measuring and improving data quality.

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CIO Business Intelligence

FEBRUARY 14, 2023

It’s clear how these real-time data sources generate data streams that need new data and ML models for accurate decisions. Data quality is crucial for real-time actions because decisions often can’t be taken back. However, a data execution strategy has to evolve for real-time AI to scale with speed.

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Ontotext

JANUARY 29, 2024

In 2023, data leaders and enthusiasts were enamored of — and often distracted by — initiatives such as generative AI and cloud migration. Without this, organizations will continue to pay a “bad data tax” as AI/ML models will struggle to get past a proof of concept and ultimately fail to deliver on the hype.

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IBM Big Data Hub

JUNE 30, 2022

The rise of data strategy. There’s a renewed interest in reflecting on what can and should be done with data, how to accomplish those goals and how to check for data strategy alignment with business objectives. The evolution of a multi-everything landscape, and what that means for data strategy.

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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. Reusable data product components and standardization. Let’s take a look.

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Smart Data Collective

JANUARY 3, 2024

We have talked about how big data is beneficial for companies trying to improve efficiency. However, many companies don’t use big data effectively. In fact, only 13% are delivering on their data strategies. We have talked about the importance of data quality when you are running a data-driven business.

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O'Reilly on Data

FEBRUARY 11, 2020

We suspected that data quality was a topic brimming with interest. The responses show a surfeit of concerns around data quality and some uncertainty about how best to address those concerns. Key survey results: The C-suite is engaged with data quality. Data quality might get worse before it gets better.

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bridgei2i

JUNE 23, 2021

4 Key Elements of Enterprise AI Strategy. Enterprise AI harnesses advanced artificial intelligence techniques to deliver organizational data, knowledge, and information. However, due to a lack of foundation to embed AI capabilities, companies cannot successfully leverage AI into their data and operational strategy.

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Data Virtualization

MAY 19, 2023

Reading Time: 11 minutes The post Data Strategies for Getting Greater Business Value from Distributed Data appeared first on Data Management Blog - Data Integration and Modern Data Management Articles, Analysis and Information.

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DataKitchen

NOVEMBER 10, 2023

Extrinsic Control Deficit: Many of these changes stem from tools and processes beyond the immediate control of the data team. Unregulated ETL/ELT Processes: The absence of stringent data quality tests in ETL (Extract, Transform, Load) or ELT (Extract, Load, Transform) processes further exacerbates the problem.

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DataKitchen

MARCH 5, 2024

The Stakeholder Confidence Crisis Relying on hope as a data accuracy and integrity strategy is fraught with risks. Stakeholders, from internal teams to external clients, seek confidence in the data they use and depend on. You will be in trouble if you are not measuring data quality or delivering error rates and SLAs.

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CIO Business Intelligence

MAY 2, 2023

Despite the best of intentions, CIOs and their organizations often struggle to deliver business outcomes from digital transformation strategies. And while KPMG reports that 72% of CEOs have aggressive digital investment strategies, McKinsey details a harsh reality that 70% of transformations fail. Five years ago, I shared that the No.

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