Blog

Read up on our technical blogs, covering technology & AI, data management and data quality, and insights from the market.

5 Steps to Build the Case for Data & Analytics Governance

5 Steps to Build a Business Case for Data and Analytics Governance

The task of creating a compelling business case for data and analytics governance is often complex and daunting. In this blog, we break down the big picture into five simple steps to follow and turbocharge your data management strategy.   Why is data and analytics governance important? Data and analytics governance is crucial for organisations

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The rising popularity of apprenticeships to kickstart a career in the IT industry

The rising popularity of apprenticeships to kickstart a career in the IT industry

Apprenticeships have long been heralded as education and study opportunities for young school leavers, acting as an entry point to certain jobs. Sometimes apprenticeships are thought of as not encouraging progression along a tailored career path for an individual. However, this is not the case at all! Within the IT industry, apprenticeships are a great

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What Is Augmented Data Quality And How Do You Use It?

  Year after year, the volume of data being generated is increasing at an unparalleled pace. For businesses, data is critical to inform business strategy, facilitate decision-making, and create opportunities for competitive advantage. However, leveraging this data is only as good as its quality, and traditional methods for measuring and improving data quality are struggling

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How to test your data against Benford’s Law 

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,

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How You’ll Know You Still Have a Data Quality Problem

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

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What Connects James Cameron, Data Catalogs and Data Science 101? CTO Insights with Alex Brown

Matt Flenley recently took some time with Alex Brown, CTO at Datactics, to find out what he’s looking forward to in the year ahead.  You mentioned the other day in our team meeting the market trends towards Master Data Management. Is there anything that you had noted here that you wanted to expand on when

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Top 5 Trends in Data and Information Quality for 2023

Discover the latest trends in data and information quality for 2023, featuring Data profiling, Data Mesh, Data Fabric, Data Governance, and more.

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

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Battling Bias in AI: Models for a Better World

Battling Bias in AI Models for a Better World

The role of synthetic data At Datactics, we develop and maintain a number of internal tools for use within the AI and Software Development teams. One of which is a synthetic data generation tool that can be used to create large datasets of placeholder information. This was initially built to generate benchmarking datasets as another

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Outlier Detection – What Is It And How Can It Help In The Improvements Of Data Quality? 

Outlier Detection

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

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