Data Quality in Financial Institutions


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

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. As someone who is obsessed with data availability— yeah, you read that right: instead of sheep, I dream about null values and data freshness these days — this is a dream come true.Why does this matter?If Big Data Strategy

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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

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.

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. In fact, most merger and acquisition plans fail miserably because of data integration challenges.Save yourself the devastating cost of a failed merger. Most companies focus on data quality as a.

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. Just as how a house built on a weak foundation will collapse, an insurance company that uses poor quality data cannot be expected to be successful. Let’s find out how data quality can make or break your insurance business. 4 Ways poor data quality affect the insurance industry?Well, Big Data

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.

Are you struggling to get started with Data Quality?   Interview with IQ International


We are pleased to be working with our media partner, IQ International on our Chief Data & Analytics Officer Brisbane event, where they will be sharing some of their work in developing best practice data quality metrics for every industry. CDAO Sydney Data and Analytics

Using Extensions to Increase Tableau Data Quality


This post is the first in a series of blogs about Tableau and our Tableau extension for data issue tracking, Tamr Steward. Tableau extensions increase functionality in Tableau, the versatile tool for data analytics and visualization. Outside extensions open new doors to increase Tableau data quality and build better dashboards. Writebacks, analytic tools to measure user engagement, and self-service tools all help increase Tableau data quality, improving dashboards.

Stop your Data Quality Project and Start your Outcome-based Data Governance Program

Andrew White

I spoke to a client recently who had this question: “I need help to develop a survey to ask our employees around the company how they regard the various subjective metrics tied to data quality.” What was the point of the data quality work?

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.

Tips to Create Effective Data Quality Rules


You know you can rule the quality of your data. Read on to learn simple but effective tips on how to make superb data quality possible. The bad news is: Low-quality data costs companies about $15 million per year, according to Gartner’s Data Quality Market Survey. So why don’t you? The good news is: Your […].

Your Guide to Data Quality Management


Setting up data quality management seems to be a blurry task? These best practices will help you improve the quality of your data and, ultimately, your decisions We show what a well-organized process looks like and enumerate the required tools.

Data Quality Assessment Is Not All Roses. What Challenges Should You Be Aware Of?


Of all data quality characteristics, we consider consistency and accuracy to be the most difficult ones to measure. 2019 Sep Opinions Challenges Data QualityHere, we describe the challenges that you may encounter and the ways to overcome them.

Data Quality and Chicken Little Syndrome

Jim Harris

The sales pitches for data quality solutions often suffer from Chicken Little Syndrome, when vendors and consultants, instead of trying to sell the business benefits of data quality , focus too much on the negative aspects of not investing in data quality , and try scaring people into prioritizing data quality initiatives by exclaiming “your company is failing because your data quality is bad!” Data Quality Debates

Finding Data Quality

Jim Harris

Have you ever experienced that sinking feeling, where you sense if you don’t find data quality, then data quality will find you? This blog post is an hommage to not only the film, but also to the critically important role into which data quality is cast within all of your enterprise information initiatives, including business intelligence, master data management, and data governance. Data Silos. Data Profiling. “I Data Qualit

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. However, as a company, sales stack, and database grow, it becomes difficult to uphold structure and governance to keep a CRM up-to-date. The result? Less organization, more confusion, and fewer deals closed. Leveraging leading industry research from industry analysts, this eBook explores how your sales team can gain back valuable time.

Balance Data Quality with Data Agility!


Data Quality vs. Data Agility – A Balanced Approach! When it comes to analytical quality versus analytical agility, we might see the issue in the same light. Consider the standard, restrictive concept of carefully gathering every piece of data, setting boundaries and giving requirements to IT or a data scientist and then waiting days or weeks to get a report. Sometimes we are so focused on perfection that we do not see the benefit of agility.

Improving Data Quality With an Efficient Data Labeling Process


A key principle behind data preparation that data scientists regularly hammer home is that of garbage in, garbage out — if your data is flawed going into a machine learning process, you are bound to receive flawed results, algorithms, and worse, business decisions.

Data Quality in Six Verbs

Jim Harris

Once upon a time when asked on Twitter to identify a list of critical topics for data quality practitioners, my pithy (with only 140 characters in a tweet, pithy is as good as it gets) response was, and especially since I prefer emphasizing the need to take action, to propose six critical verbs: Investigate , Communicate , Collaborate , Remediate , Inebriate , and Reiterate. 1 — Investigate Data quality is not exactly a riddle wrapped in a mystery inside an enigma.

Data quality: The key to building a modern and cost-effective data warehouse

IBM Big Data Hub

Turning raw data into improved business performance is a multilayered problem, but it doesn’t have to be complicated. To make things simpler, let’s start at the end and work backwards. Ultimately, the goal is to make better decisions during the execution of a business process. This can be as simple as not making a customer repeat their address after a hand-off in a call center, or as complex as re-planning an entire network of flights in response to a storm

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 DataOps enabled Standard Bank to gain data quality and agility during changing market conditions

IBM Big Data Hub

Follow @IBMAnalytics. DataOps journey

How in-line address data quality delivers business ready data for AI initiatives

IBM Big Data Hub

Imagine opening your mailbox and seeing a letter addressed to “current resident,” or having your financial institution’s AI powered digital assistant inform you that your replacement card is on its way to your old address

Data Conversations Over Coffee with Matthew Bernath


Data & Coffee - Two Things That Demand The Highest Quality. Data and Analytics Data Quality Training Online

Infographic: How Can Data Quality Be Improved?


Data needs to be valuable (high quality, labeled, and organized) to drive machine learning model success. This infographic reveals some of the challenges data leaders face when it comes to data quality as well as a specific focus on the need for data labeling through active learning.

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.

Video: Data Conversations Over Coffee with Maciej Kaliszka (DQT)


In episode 6 of Data Conversations Over Coffee we talk to Maciej Kaliszka about building a fully accredited Data University! Data and Analytics Data Quality Training Online

Video: Data Conversations Over Coffee with Caroline Carruthers (DQT)


In episode 5 we talk to the co-author of two data focused books - Caroline Carruthers of Carruthers & Jackson. Data Quality Training Online

Video: Data Conversations Over Coffee with Ben Jones (DQT)


This is episode 3 of Data Conversations Over Coffee and we're speaking to Ben Jones. Data and Analytics Data Quality Training Online

Video: Data Conversations Over Coffee with Alex MacPhail


In episode 7 of Data Conversations Over Coffee we talk to Alex MacPhail who is a pilot and keynote speaker on leading high performing teams. Data and Analytics Data Quality Training Online DataCon Africa Live

Data Management on Display at Informatica World 2019

David Menninger's Analyst Perspectives

Under that focus, Informatica's conference emphasized capabilities across six areas (all strong areas for Informatica): data integration, data management, data quality & governance, Master Data Management (MDM), data cataloging, and data security. Big Data Data Quality Master Data Management Data Governance Data Management Informatica data lakes Informatica World Data Storage

How to Convince Stakeholders That Data Governance is Necessary


You may already have a formal Data Governance program in place. Or … you are presently going through the process of trying to convince your Senior Leadership or stakeholders that a formal Data Governance program is necessary. Maybe you are going through the process of convincing the stakeholders that Data […]. Then again, perhaps you don’t.

Video: Data Conversations Over Coffee with Abboud Ghanem (DQT)


We've been working together in the data analytics community across the Middle East & Africa for the past 3 years and have formed a strong friendship over that time. Data and Analytics Data Quality Training OnlineIn episode 4 Abboud shares how coffee takes him on a journey, his passion for analytics & the need to bring humanity to leadership during a crisis. Every now and then you meet someone you just gel with. Abboud is one of those people for me.

Broken Data – What You Don’t Know Will Hurt You – Part 1


The first step to fixing any problem is to understand that problem—this is a significant point of failure when it comes to data. Most organizations agree that they have data issues, categorized as data quality. Organizations typically define the scope of their data problems by their current (known) data quality issues (symptoms).

All in the Data: Data is Everybody’s Job


What happens when people who should be accountable for producing quality data as part of their job make it clear that they want nothing to do with producing data? What happens when the data they should produce is important in improving […].

What is a Data Management Platform?


Digital media is growing more and more complex by the day, and as a result, so is the data generated and harvested around the world.

Make An Impact: Hidden Reasons Why Your Data Analysis Has No Value


In most of our organizations we have people doing data analysis all over the place. From very technical SQL queries and cubes to the more mundane spreadsheet-based number crunching, we have no shortage of data activity going on. It would be too easy to say that the reason organizations fail to fully capitalize on this […].

DAMA International Community Corner: August 2020 Update


Welcome to DAMA Corner, a source of information for data management professionals here in the industry leading publication for people interested in learning about data administration and data management disciplines and best practices.

All in the Data: Data Governance Made Easy


Organizations that have implemented Data Governance programs, or Information Governance, Data/Information Management or Records Management programs will be the first to tell you that these data disciplines are not easy to operationalize. Data Management requires that the organization care for data as an asset. Managing data as an asset sounds pretty complicated. Data Governance involves […].

Data Management 20/20: Data Governance Challenges in a Digital Society


The reversal from information scarcity to information abundance and the shift from the primacy of entities to the primacy of interactions has resulted in an increased burden for the data involved in those interactions to be trustworthy. If service and results are substandard or wrong, the reputation of the company can more quickly than ever […].

Steps to an Effective Data Governance Structure


The quality of data used in business is more important now than ever before. Accordingly, in order for organizations to deliver good business results, their data must be accurate, and the use of that data must be governed through policy and monitoring. How do business leaders prevent data errors and ensure quality governance?