6 ‘P’s For A Data Quality Framework

DataFloq

Why do you need data quality ? The same goes for data. If we are going to generate revenue from our data, reduce risk, nurture trust for people to reuse the data so they dont create their own Shadow IT with their multiple spreadsheet copies of data.

How to Stop Ignoring Data Cleansing & Take Control of Your Data Quality

DataFloq

Fun fact – data cleansing is often ignored. Executives and decision-makers aren’t aware of data quality problems while mid-level managers and juniors find it irksome to tackle. Data cleansing starts with accepting there is a data quality problem.

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Machine Learning-Based Data Quality — Next Frontier for Data Management

DataFloq

Enhancing data quality using machine learning. Regardless of how accurate a data system you design, 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.

Building a Data Platform: 7 Signs It’s Time to Invest in Data Quality

DataFloq

One of the most frequent questions I get from customers is: when does it make sense to invest in data quality and observability? The reality is that building a data platform is a multi-stage journey and data teams have to juggle dozens of competing priorities.

Supply Chain Planning Maturity – How Do You Compare to Peers?

Today's supply chains are networked, global ecosystems. An event upstream in a different country or region can cause considerable disruption downstream. The COVID-19 pandemic is an extreme example of how this unfolds in practice. How prepared are supply chain teams to react and recover, from a planning maturity stance? Download this report to get exclusive insights on planning maturity!

Winning In Consumer Packaged Goods With Data Quality

DataFloq

In light of these hurdles, data has proven to be critical to survival and growth. But, collecting data alone isn’t sufficient. It isn’t about quantity, it’s about quality. Data quality determines its value and potential benefits. Data As The Foundation For Success.

What I Learned from Executing Data Quality Projects

The Data Administration Newsletter

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 […].

Data Quality: Volume, interdependencies can create big problems

DataKitchen

The post Data Quality: Volume, interdependencies can create big problems first appeared on DataKitchen. News News / PR

Data Quality Is In the Eye of the Beholder

The Data Administration Newsletter

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 […].

Data Quality — You’re Measuring It Wrong

DataFloq

This article was first posted on Towards Data Science.One of our customers recently posed this question:“I would like to set up an OKR for ourselves [the data team] around data availability. Big Data Strategy

3 Points To Place Checks For Data-Quality

DataFloq

Data is the most valuable asset in the digital economy. Be it nurturing existing clients or expanding into new territories, data is the foundation on which new initiatives are built and execution is reviewed against. Data Ingestion. Big Data Technical

How to Overcome the Pain Points of Your CRM

CRM software is a powerful tool when used correctly, yet another obstacle to a sales team’s efficiency when it’s not. Leveraging research and commentary from industry analysts, this eBook explores how your sales team can get back valuable time by overcoming some pain points with your CRM, such as low adoption rates, integrations, and data quality.

Data Quality Problems Everywhere You Look

The Data Administration Newsletter

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?

How Machine Learning Transforms Data Quality And Operational Necessities

DataFloq

Machine Learning has the tendency to evoke extreme reactions – some consider it a superpower while for others, machine learning is just another fad. That said, research has shown that 76% of enterprises have prioritized AI and Machine Learning initiatives over other IT projects.

Data Management’s Next Frontier is Machine Learning-Based Data Quality

The Data Administration Newsletter

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.

Dont Acquire a Company Until You Evaluate its Data Quality

DataFloq

The companies join workforces, systems, infrastructure, and data to become a new, more powerful, more valuable, more effective entity. That is only until they realized they overlooked or underestimated the key issues with data, IT infrastructure & integration plans.

Data Quality Can Make Or Break Your Healthcare Business

DataFloq

Whether it’s handwritten by a doctor on a sheet of paper or entered into a computer system, data plays a crucial role in healthcare. At an individual level, patient data determines the course of treatment. This is where data quality comes in. Big Data

Best Practices for a Marketing Database Cleanse

As frustrating as contact and account data management can be, this is still your database – a massive asset to your organization, even if it is rife with holes and inaccurate information. Entrusting a vendor to help maintain its accuracy and completeness is no ordinary engagement. Download ZoomInfo’s latest data-driven eBook aimed to help marketing leaders understand the best practices around choosing a B2B contact data provider.

Data is Risky Business: Data Quality Discussion about Data Ethics

The Data Administration Newsletter

The Data Ethics Conundrum The recent DAMA EMEA conference was a valiant effort to connect the DAMA membership in the EMEA region through an innovative virtual conference format. One of these polls asked, “Are Data Ethics Principles Universal?”

Why Data Quality Matters

The Data Administration Newsletter

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. It is always the result of intelligent effort.”

The state of data quality in 2020

O'Reilly on Data

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.

How to Fix Your Data Quality Problem

DataFloq

Data quality is top of mind for every data professional — and for good reason. Bad data costs companies valuable time, resources, and most of all, revenue. So why are so many of us struggling with trusting our data? The data landscape is constantly evolving, creating new opportunities for richer insights at every turn. Not surprisingly, one of the most common questions customers ask me is “what data tools do you recommend?”. Big Data Strategy

How to Overcome the Pain Points of Your CRM

When used effectively, a CRM can be the life blood of your sales team – keeping everyone organized, efficient, and at peak productivity. Leveraging leading industry research from industry analysts, this eBook explores how your sales team can gain back valuable time.

Preserving Data Quality is Critical for Leveraging Analytics with Amazon PPC

Smart Data Collective

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.

Improving Data Quality for the Insurance Industry – Why and How

DataFloq

we all know, insurance is a customer centric industry and highly dependent on data. It would be fair to call data the foundation for the industry. Let’s find out how data quality can make or break your insurance business. Big Data

Video: Why Businesses Struggle with Data Quality

Corinium

Matthew Bernath, Head of Data Analytics at Rand Merchant Bank, discusses why ensuring data is high quality remains a key challenge for businesses today with Corinium's Craig Steward. Data and Analytics

Data Quality: Making Change a Choice

DataFloq

Big DataIn the modern world, nothing stays the same for long. We live in a state of constant change; new technologies, new trends and new risks. Yet it’s a commonly held belief that people don’t like change. Which led me to wonder, why do we persist in calling change management initiatives “change management” if people don’t like change. In my experience, I have not found this maxim to be true.

Forrester Research Report: How Sales and Marketing Intelligence Drive Improved Business Outcomes

In 2019, DiscoverOrg commissioned Forrester Consulting to evaluate sales and marketing intelligence practices in the B2B space. The primary takeaway? Forrester found only 1.2% of companies achieved a score indicating maturity in data management practices. However, organizations are fighting back - and winning.

Expanding Role of Data Governance, Metadata Management, and Data Quality

The Data Administration Newsletter

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.

How to Deliver Data Quality with Data Governance: Ryan Doupe, CDO of American Fidelity, 9-Step Process

Alation

Several weeks ago (prior to the Omicron wave), I got to attend my first conference in roughly two years: Dataversity’s Data Quality and Information Quality Conference. Ryan Doupe, Chief Data Officer of American Fidelity, held a thought-provoking session that resonated with me.

Controlling Data Quality: Tips and Tools

Dataiku

Only 8% of CDOs are content with the quality of data at their disposal. Data needs to be valuable, thus of high quality , to drive machine learning model success.

Solving the Insurance Industry’s Data Quality Problem

Corinium

Using data to inform business decisions only works when the data is correct. Unfortunately for the insurance industry’s data leaders, many data sources are riddled with inaccuracies. Data is the lifeblood of the insurance industry. Data and Analytics

A Guide to Better Data Quality

Without high quality data that we can rely on, we cannot trust our data or launch powerful projects like personalization. In this white paper by Snowplow, you'll learn how to identify data quality problems and discover techniques for capturing complete, accurate data.

Data Quality: The Good, The Bad, and The Ugly

KDnuggets

Incorrect or unclean data leads to false conclusions. The time you take to understand and clean the data is vital to the outcome and quality of the results. Data Quality always takes the win against complex fancy algorithms. 2022 Jan Opinions Data Science

Data Quality in the Age of AI: A User Story

Dataiku

Today, more than 90% of AI practitioners experience significant cascading data errors , and poor data quality is estimated to cost companies 20% of revenue. The bottom line: bad data is ubiquitous and costly, and it also reduces organizations’ overall AI productivity.

Who Is Responsible for Data Quality Within an Enterprise?

Dataiku

Poor data quality is troublesome for a myriad of reasons, from analyst productivity lost, to bad reporting and decision making, to potential negative impacts on revenue.

OCDQ Radio on Data Quality

Jim Harris

OCDQ Radio is an audio podcast about data quality and its related disciplines, produced and hosted by Jim Harris. Podcast Episodes on Data Quality. OCDQ Radio Podcasts Data QualityThis podcast is no longer an active project, meaning not only do I rarely publish a new episode, but its episodes are only available to listen to on this website and no longer distributed on platforms such as Apple Podcasts and Google Podcasts.

Why B2B Contact and Account Data Management Is Critical to Your ROI

64% of successful data-driven marketers say improving data quality is the most challenging obstacle to achieving success. Given data’s direct impact on marketing campaigns, reporting, and sales follow-up, maintaining an accurate and consistent database is a top priority for B2B organizations. This latest eBook aims to help marketing leaders understand the impact of data management on their company’s ROI.

Addressing CRM Data Quality with Dataiku

Dataiku

Using machine learning (ML) to predict customer growth, churn, and to find insights in the data is not only a trendy topic, but also something that can bring a lot of value.

Alation & Bigeye: A Potent Partnership for Data Quality

Alation

Alation and Bigeye have partnered to bring data observability and data quality monitoring into the data catalog. Read to learn how our newly combined capabilities put more trustworthy, quality data into the hands of those who are best equipped to leverage it.

Alation + Soda: Dynamic Data Quality with the Data Catalog

Alation

Alation and Soda are excited to announce a new partnership, which will bring powerful data-quality capabilities into the data catalog. Soda’s data observability platform empowers data teams to discover and collaboratively resolve data issues quickly.

The Importance of Data Quality in Financial Reporting

Insight Software

Data quality has always been at the heart of financial reporting , but with rampant growth in data volumes, more complex reporting requirements and increasingly diverse data sources, there is a palpable sense that some data, may be eluding everyday data governance and control.

The Alation State of Data Culture Report - Q1 2021

Companies are expected to spend nearly $23 billion annually on AI by 2024. What could go wrong? This report explores AI obstacles, like inherent bias and data quality issues, and posits solutions by building a data culture.