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Data wrangling is often used to describe what data engineers do. However, a universally accepted definition of the concept has proven difficult to find. It was therefore fortuitous that I came across this piece on Simplilearn titled “What Is Data Wrangling? Overview, Importance, Benefits, and Future.” It shares some interesting and insightful points and so …
My colleague and I were fortunate enough to be invited to attend the recent Corinium CDAO Melbourne 2024 conference held from 2-4 September 2024. Corinium has an interesting approach to this annual event by alternating between keynote and breakout sessions, guided panel discussions, and interactive fireside chats. Such a structure makes for an insightful and …
Last month, I explored the challenges created by data silos and how pragmatic approaches like a data lakehouse architecture and data steering teams can assist in breaking down the silos. In this month’s post, my attention on the topic turns to more strategic drives that can help achieve better enterprise-wide data sharing and overcome the …
Data silos are pervasive in organisations around the world. At many of the companies where I have worked, these data silos have made it difficult to ensure system integration, data governance, and effective reporting. Following an insightful industry piece I recently came across, for my blog article this month, I decided to focus on and …
Given the growing adoption of artificial intelligence (AI), and companies across industry sectors wanting to become truly data-driven, having a Chief Data Officer (CDO) becomes non-negotiable. However, not every organisation truly understands what this role encompasses.
I recently had the privilege to attend the Data and Analytics in Healthcare conference hosted by Corinium Intelligence in Australia. Following this, I wanted to use my blog piece this month to discuss some of the key lessons and insights shared during the event. I’ll jump straight in. Data governance and ethics Of course, it …
Do you know where your food comes from? Did the farmer use pesticides? Did the transport company spray preservative chemicals over your food? Did they keep it appropriately refrigerated? Would you eat food from sources you don’t trust? The same applies to data. Do you know what the lifecycle of your data entails? Was it …
Despite the hype surrounding generative Artificial Intelligence (GenAI), I am finding in my industry reading that many industry analysts are predicting that data quality (one of my favourite topics) will remain a key priority for this year – especially when it comes to data management and governance.
Last month I addressed how data quality is perceived by different specialists inside the organisation. This month, I turn the spotlight onto what makes modern data quality management different from traditional approaches. Edwin Walker’s Data Science Central article ‘Difference between modern and traditional data quality’ provides an excellent starting point.
The quality of the data we work with has a significant impact on the quality of the insights we can extrapolate for the business. Following on from my recent mini-series on the evolving data-related roles, it was interesting to come across Edwin Walker’s article on Data Science Central titled: ‘How do different personas in an …
