Assuring Data Quality: How to Build a Serverless Data Quality Gate on AWS


Data is a vital element in business decision-making. Modern technologies and algorithms allow for processing and storage of huge amounts of data, converting it into useful predictions and insights. But they also require high-quality data to ensure prediction accuracy and insight value. In today's world, the importance of data quality validation is hard to overestimate. Great Expectations – A Data QA Tool of Choice.

Data quality: What and why is it important?


With the internet producing quintillions of readily available information per day, you could be forgiven to think that data is losing its value. Virtually all companies making good in various niches are where they are because of data. Importance of data quality.


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The Right Way to Measure ROI on Data Quality


Last week, I was on a Zoom call with Lina, a Data Product Manager who oversees a data quality program for her organization. Her team is responsible for maintaining 1000s of data pipelines that populate many of the company's most business critical tables.

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Why Is Data Quality Always an Afterthought? Strategies to Master Data Quality Management


For probably the umpteenth time, we use the term “garbage in, garbage out” when summarizing problems with data quality. Various industry studies have uncovered the high cost of bad data, and it’s estimated that poor data quality costs organizations an average of $12 million yearly.

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!

6 ‘P’s For A Data Quality Framework


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.

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


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.

Winning In Consumer Packaged Goods With Data Quality


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.

Top 5 Ways Poor Data Quality is Sabotaging Businesses


Every business collects data about their customers including their names and addresses, phone numbers, email addresses, order history and preferred payment modes. However, it isn't the amount of data collected that determines its usefulness but the quality of this data. If your data doesn't match high-quality standards, it could harm your business initiatives. Poor quality data can cost organizations up to $12.9 They aren't fabricating data.

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


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.

Data Quality in Financial Institutions


Datacon Africa DataCon Africa Insights Data and AnalyticsIn the last decade regulatory requirements in financial services increased significantly.

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: the Silent Assassin of the Modern Data Stack


If data is the new oil, then high-quality data is the new black gold. Just like with actual oil, if you don't have good data quality, you're not going to get very far. So, what can you do to make sure your data is up to par? Data lakes, Data pipelines, and Data Warehouses have become core to the modern enterprise. Once observability has been achieved, how can we be confident that the data within is trustworthy?

Data Quality: the silent assassin of the modern data stack


If data is the new oil, then high-quality data is the new black gold. Just like with actual oil, if you don't have good data quality, you're not going to get very far. So, what can you do to make sure your data is up to par? Data lakes, Data pipelines, and Data Warehouses have become core to the modern enterprise. Once observability has been achieved, how can we be confident that the data within is trustworthy?

Thoughts on Data Literacy & Data Quality

The Data Administration Newsletter

Last week, we presented a webinar in our Data Governance — Best Practices series on data quality.

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 — You’re Measuring It Wrong


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

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.

3 Points To Place Checks For Data-Quality


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

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?

Dont Acquire a Company Until You Evaluate its Data Quality


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 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 […].

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.

How Machine Learning Transforms Data Quality And Operational Necessities


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 Quality Can Make Or Break Your Healthcare Business


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

Why Data Quality Programs Fail to Deliver Results


Fortune 1000 organizations spend approximately $5 billion in total each year to improve the trustworthiness of data. Yet, only 42% of the executives trust their data.

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.”

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.

How to Fix Your Data Quality Problem


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

Improving Data Quality for the Insurance Industry – Why and How


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

Applied Energy Services doubles down on data quality


Data analytics and business intelligence are critical to every business, but especially important in the energy industry, as information is channeled from consumers and commercial clients related to usage that feeds into AES’ sustainability and services planning. Analytics, Data Management

Data Quality: Volume, interdependencies can create big problems


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

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 Fundamentals Expert Panel


Join Lior Gavish, co-author and Monte Carlo co-founder, Oct 12 @ 1 PM ET, as he explores the latest in data quality techniques with a panel of some of the foremost experts.

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?”

Alation 2022.2: Open Data Quality Initiative and Enhanced Data Governance


Additionally, a set of key features will accelerate data governance and simplify the security of sensitive metadata. Our Data Quality Journey. The perennial problem of using data to make decisions, as coined by George Fuechsel, is garbage in, garbage out.

Video: Why Businesses Struggle with Data Quality


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

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.

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.

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.

The Data Quality Hierarchy of Needs


Just as Maslow identified a hierarchy of needs for people, data teams have a hierarchy of needs, beginning with data freshness; including volumes, schemas, and values; and culminating with lineage. KDnuggets Originals Data Science

Data Quality: Making Change a Choice


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.

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.