We are currently in an exciting area and time, where Machine Learning (ML) is applied across sectors from self driving cars to personalised medicine. Although ML models have been around for a while – for example, the use of algorithmic trading models from the 80’s, Bayes since 1700s – we are still in the nascent …
The Importance of Data Quality in Machine Learning Read More »
One of the most important aspects of data quality is being able to identify anomalies within your data. There are many ways to approach this, one of which is to test the data against Benford’s Law. This blog will take a look at what Benford’s Law is, how it can be used to detect fraud, …
Despite a seemingly healthy green glow in your dashboards and exemplary regulatory reports, you can’t help but sense that something is amiss with the data. If this feeling rings true for you, don’t worry – it may be an indication of bigger issues lurking beneath the surface. You’re not alone. In this blog we’ve taken …
How You’ll Know You Still Have a Data Quality Problem Read More »
Alexandra Collins, Product Owner at Datactics, recently spoke on an A-Team webinar on the subject of how to build a data quality control framework. In case you missed it, here is everything you need to know about building a data quality control framework using the latest tools and technologies. What are the drivers of change …
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In this blog post, our Head of Marketing, Matt Flenley, takes a closer look at the latest trends in data and information quality for 2023. He analyses predictions made by Gartner and how they’ve developed in line with expectations to provide insight into the evolution of the market and its various key players. Automation and …
Top 5 Trends in Data and Information Quality for 2023 Read More »
Identifying outliers and errors in data is an important but time-consuming task. Depending on the context and domain, errors can be impactful in a variety of ways, some very severe. One of the issues with detecting outliers and errors is that they come in many different forms. There are syntactic errors, where a value like …
Outlier Detection – What Is It And How Can It Help In The Improvements Of Data Quality? Read More »
Data quality may not be viewed as a particularly attractive topic of conversation at a dinner party or a company event, yet it is a critical step for organisations to maximise the value of their information and subsequent decision-making. It is therefore imperative that data leaders make every attempt to raise awareness and educate on …
In March 2022 Datactics took advantage of the offer to visit a local high school to discuss AI Ethics and Machine Learning in production.
The previous two editions of this blog series provided an overview of the Gartner Magic Quadrant from the perspective of someone relatively new to the world of data management, defining what it really means for a scaling business like Datactics to be recognised by Gartner.
Data in a Changing World The Insurance industry traditionally uses data to inform decision-making and manage growth and profitability across marketing, underwriting, pricing and policy servicing processes. However, like most established financial institutions, insurance companies have many data repositories and different teams managing analytics functions. Traditionally, they also struggle to share this information or communicate …
Data Quality fundamentals driving valuable Data Insights in Insurance Read More »
of this evolution is the establishment of ‘self-service’ data quality – whereby data owners and SMEs have ready access to robust tools and processes, to measure and maintain data quality themselves, in accordance with data governance
policies.
The drivers and benefits of a holistic, self-service data quality platform | Part 1 Change There has been increasing demand for higher and higher data quality in recent years – highly regulated sectors, such as banking have had a tsunami of financial regulations such as BCBS239, MiFID, FATCA, and many more stipulating or implying exacting …
In the previous edition of this series, we explored the Gartner Magic Quadrant from the perspective of a newcomer to the data management industry
Last month, we at Datactics were delighted to announce that we had been recognised in this year’s edition of the Gartner Magic Quadrant for ‘Data Quality Solutions’. This is a remarkable achievement for everyone associated with the company, as we make our first appearance on the quadrant, gaining industry recognition for our sophisticated technology and …
Gartner Magic Quadrant Blog 1 – What is the Gartner Magic Quadrant? Read More »
Demand for better quality data has never been higher. Stuart Harvey, CEO of Datactics, writes that self-service data quality could be the key that unlocks significant competitive advantage for financial firms.
Written by Daniel Browne, Machine Learning Engineer Defining data quality rules and collection of rules for data quality projects is often a manual time-consuming process. It often involves a subject matter expert reviewing data sources and designing quality rules to ensure the data complies with integrity, accuracy and / or regulatory standards. As data sources …
Data quality refers to how fit your data is for serving its intended purpose. Good quality data should be reliable, accurate and accessible.
Introduction Getting into shape is a big focus of summer advertising campaigns, where we’re all encouraged to eat, drink and do the right things to keep our bodies and minds on top form. You’ll be relieved to read that at Datactics we’re far more concerned about the health of your data, so open that packet of cookies, pour yourself …
Self-service data quality & matching specialists routinely winning awards and recognition for our software, company culture and customer satisfaction.