Weekly News Digest: 8th – 12th August 2022 | Harnham Recruitment post

This is Harnham's weekly news digest, the place to come for a quick breakdown of the week's top stories from the world of data & analytics.


Artificial Intelligence (ai) has been a popular topic for years now, and the technology continues to grow and create buzz across most industries globally.AI gives computers the ability to learn and work on their own, making decisions based on the data provided. One of the key reasons for AI's immense growth in the past few years is the ability to automate jobs that are otherwise time-consuming or tedious for humans to perform. Because of this, there is substantial demand for ai skills and professionals worldwide.So, what are the crucial skills needed to build a successful career in ai? Some examples are:Programming skills and languages (python, r, java and c++)Libraries and frameworksMathematics and statisticsMachine learning and deep learningNatural language processing and computer visionData science and data analysisSoft skills (collaboration, communication and critical thinking skills)As organisations become more aware of how this technology can improve their workflows, the demand for ai experts will continue to grow. Those willing to master the technology will be able to open new doors for themselves and their companies.To read more about this, click here.


By 2022, the entire enterprise data volume is expected to exceed 2.02 petabytes which means that businesses operating in extremely data-intensive environments will require more powerful data management capabilities than ever before. Capabilities will need to monitor, manage, store, access, secure, and share data in a simplified and standardised manner.Creating successful data governance architecture can help to maximise data value, minimise risks, and eliminate unnecessary operating costs.Here are five key best practices for accomplishing data governance success:Define the proper proof in alignment with the right people:Build the roadmap that ensures data can always be trustedBecome consistently compliant with regulatory requirementsEvaluate risks across the boardBring the right data management platform to the table.Data governance is not a one-time strategy - it's an ongoing process that involves business-wide tasks, responsibilities, and protocols. Data is one of the most valuable assets for businesses to make important decisions around risk mitigations and the governance of data should be a high priority.To read more about this, click here.


As healthcare continues to utilise the many benefits of technology, such as artificial intelligence (AI), machine learning (ML), and big data, how that data is secured and governed is becoming increasingly important.The data spectrum model demonstrates how data, whether small, large, personally or commercially owned, can be used and reproduced depending on the way that data is licensed. This model can help data specialists understand the risks of securing healthcare data in an industry where cybersecurity attacks have tripled since 2018.In addition to models such as the data spectrum model, data specialists must also explore how closely data sharing and data protection can function together, as there must be a balance of security, openness and citizen rights.While patient consent and assent are required, the following methods can be used to secure and store data safely:End-to-end encryption/data encryptionUse of a virtual private network while accessing patient recordsFrequently changing passwords to avoid hacking of an accountImplementing two-factor authentication for health professionals while accessing records.To read more about this, click here.


Machine Learning (ML) is gaining popularity rapidly in the business world as companies turn to data science to help them enhance their operational procedures. Tools like ml or ai can automate, integrate, and organise data in ways that humans cannot.The integration of ml into business strategies is often hindered by the lack of expertise internally, however, it is well worth the investment of experts and training because of the obvious benefits it can have. Here are six of the top business benefits of ML:Automates real-time chatbot agentsFacilitates accurate medical predictions and diagnosesSimplifies time-intensive documentation in data entryProvides more accurate rules and models for moneyClarifies market research and customer segmentationDetects fraud.Automation and ai are becoming more essential tools for businesses in their day-to-day operations, and ml is one of the most widely used. Although the installation of ml can be time-consuming and expensive, the benefits and advantages of the technology can significantly benefit a company.To read more about this, click here.We've loved seeing all the news from data & analytics in the past week, its a market full of exciting and dynamic opportunities. To learn more about our work in this space, get in touch with us at info@harnham.com.

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