Weekly News Digest: 29th March - 1st April 2021

Joe Gibbs our consultant managing the role
Author: Joe Gibbs
Posting date: 4/1/2021 3:51 PM
This is Harnham’s weekly news digest, the place to come for a quick breakdown of the week’s top news stories from the world of Data & Analytics.   

Forbes: 5 converging trends driving the need to know and trust your users online


Over the past 12 months, digital transformation has boomed. In this new remote era, more and more people are taking to their phones or laptops to undertake traditionally ‘offline’ tasks. This uptake of digital is evidenced through a recent study by J.D Power which states that nearly a third of new account opening, such as bank accounts, are done via a website of mobile app, a 50 per cent increase compared to only a year ago. 

While efficient and much faster than consumers having to go into a physical bank, there are many dangers that lay in wait for both brand and consumer. From data breaches to the dark web, privacy regulations to fraud, businesses much ensure they have strong identity orchestration capabilities to keep users and their identities safe online. 

Read more on this article here.

TechCrunch: Facebook makes it easier to view a non-algorithmic news feed


Any social media platform’s algorithm is the bane of any users’ experience. The way in which news feeds are shaped are purely shaped by the company’s own algorithms which, very often, are not reflective of what we want to see. Businesses have also struggled for many years to get themselves seen and heard by the correct audience on sites like Facebook due to the ever-changing and, frankly, confusing algorithm it employs.  

However, it was announced this week that Facebook have finally created a feature that allows users to see a version of their news feed that isn’t algorithmically moulded. This includes aspects such as a ‘favourites’ view that displays posts from up to 30 of your favourite friends and pages, as well as a ‘most recent’ view which shows posts in chronological order.

Read more on this here.

Builtin: Nine SMS marketing tools to know 


Many brands choose to use SMS Marketing over email, as it has been shown to be more effective. While email open rates usually sit around 20 per cent, SMS open rates beat this three-fold with usual open rates of around 82 per cent. Additionally, SMS marketing is a much more human, intimate way of talking to consumers, an important aspect of communication emails still miss. 

This informative article by Builtin helps those new to SMS marketing by guiding them through nine of the best tools to use to get started.

  • Postscript
  • Attentive
  • SMSBump
  • SlickText
  • SimpleTexting
  • Octane AI
  • Klayviyo
  • Omnisend
  • Subtext

While all are used to send texts and facilitate relationships between brand and consumer, each is designed differently in order to best serve the brand’s needs and wants from this style of marketing. 

To learn about each platform, click here.  

Praxis: How to prepare for a Data Engineering interview


Preparation for any interview is key. The more learning and research you have undertaken, therefore the more knowledge you can take to the table, the more likely your interviewer is to sit up and listen. So, what exactly should you focus on if you’re heading into an interview for a Data Engineering role? This brilliant article from Praxis gives eight great pointers, here a few examples: 

  • Programming and coding skills – Ensure you know how to use optimal data structure and algorithms to handle potential data issues.
  • Know your tools – Get acquainted with popular open-source libraries such as Spark, Pandas, Hadoop and Kafka. Languages are important too, knowledge around Java, Python, HTML, CSS and JavaScript will set you apart from the competition.
  • Be a pro at SQL – SQL is one of the most essential skills for any Data Engineer, make sure you know it inside out. 

To learn what else you need to know to be best prepared for your Data Engineer interview, read the full article here

We've loved seeing all the news from Data & Analytics in the past week, it’s 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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The Five Ws Of Becoming A Data Scientist

The demand for Data Scientists has dramatically increased over the past five years. Research has shown that skills such as Data Science, SQL databases, Big Data and Machine Learning have been the most sought after by British employers in this period, with demand tripling by over 200 per cent.  This growth has been accelerated since the start of the pandemic. As businesses faced an unprecedented crisis, with no prior knowledge of how to manage, adapt or survive, leaders needed to turn to data to make informed business decisions to help them navigate the unknown.  Even though we are already now on the path to economic recovery, this need for data-driven knowledge won’t dissipate any time soon. From being able to create in-depth risk forecasts to gathering consumer sentiment, creating intelligent solutions, and using automation to reduce bottom-line costs; Data Science’s role will continue to be the backbone of success as companies steer through this ‘new normal’.  Nevertheless, despite the ever-growing appetite for Data Scientists and the number of available roles and opportunities escalating day-by-day, businesses are coming up against the brick wall of a shortage of specialists. According to IBM, Data Science roles remain unfulfilled for 45 days or longer and the UK is having to combat a £2bn Data skills shortage.  So, as a student, graduate or current Data Scientist looking to move into a more niche role, what are the key traits, skills and experiences, or the five Ws, you need to have to ensure you not only land your dream job, but help plug the increasing skills gap? Who can be a Data Scientist? Anyone can train to become a Data Scientist, and the industry is working hard at improving its attraction and retention of a diverse workforce.  Despite traditionally being a very male-dominated sector, research Harnham undertook in August 2020 found that Data & Analytics’ gender divide is slowly but surely closing. 30 per cent of women now make up the industry, a big leap from 18 per cent in 2019.  What skills do you need? Data Scientists are traditionally required to have at least an undergraduate Bachelors’ degree, usually across science, technology, or statistics. However, the majority will continue to go on to get a Master’s (88 per cent) or PHD (46 per cent) level qualifications.   Nonetheless, as more businesses have become attuned to how this level of education can cause significant gaps in the number of diverse candidates, other routes into the industry have been made available, such as apprenticeships and work experience.  Technical skills will also stand you in brilliant stead, from coding languages to machine learning and AI techniques. While not a must-have, a lot of employers, especially post-COVID, will be looking to hire talent that can get started without too much training.  When should I apply for a role? In this new normal, as mentioned, employers are looking for candidates who are ‘work-ready’. So, to position yourself above the rest of the competition, make sure you apply for roles when your skills and knowledge are at the highest standard they can be.    Where could I work as a Data Scientist? The pandemic has completely skewed the normal working routines of most industries, but especially Data Science. Whereas, usually, the most attractive jobs would be based in London, now, with the correct equipment and support in place, those working within the field can work from anywhere, paving the way for a much more flexible workforce and a steep increase in remote working.   Why should I work as a Data Scientist? As a Data Scientist, you’ll never be short for opportunities. As more and more businesses look to implement Data Science into their working model to help make data-driven decisions which not only provide clarity but help reduce costs and positively affect the bottom-line, demand for skilled professionals will only grow.   Of course, job security isn’t the only perk of becoming a Data Scientist: You can also expect to receive a competitive salary.You’ll be part of an exciting and ever-evolving industry, no two days will ever be the same.Your skillset will mean you’re never limited – the business world is your oyster!  Data Science is an extremely varied career path to take, and its role within society has grown vastly, especially over the past year. For anyone looking to enter the industry, plug the skills gap or embark on something completely new, this could be a step in the right direction for you.  If you're interested in working in Data Science, or building out your team, we may be able to help. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more. 

Weekly News Digest: 12th - 16th April 2021

This is Harnham’s weekly news digest, the place to come for a quick breakdown of the week’s top news stories from the world of Data & Analytics.      Express Pharma: The five biggest data challenges for life sciences Life Sciences has grown exponentially over the past 12 months. As the COVID-19 pandemic devastated the world, Life Science companies were in a race against time to create a life-changing vaccine and help us all back on the road to recovery.  In 2019, the Life Science market was valued at around $7.5bn. After this year’s influx of activity, the market is estimated to grow by over double in the next decade, reaching $18bn by 2030.  However, despite the positive growth the industry has had, this doesn’t mean Life Sciences will be free of challenges. In fact, with such a spike in the amount of data held by so many Life Science companies as they tried to work on a vaccine, data storage is now one of the main concerns for anyone working within the field.  In this article by Express Pharma, Vimal Venkatram, Country Manager for Snowflake India, highlights the five key data hurdles Life Sciences will continue to have to overcome in the following decade. These include data performance, data exchange and collaboration, data quality, data management and scaling, and regulatory compliance.  Read the full story here.  Harnham: How can organisations tap into the huge pool of neurodiverse data talent? For many companies, the past year has led to an increased focus on diversity and inclusion within businesses – a fantastic step forward. However, when we think of diversity, we usually assume people are talking about gender, ethnicity, sexuality and perhaps even physical disability. One area that is regularly missed from discussion is that of neurodiversity.  An umbrella term coined by sociologist, Judy Singer, neurodiversity can cover a wide range of neurological conditions such as dyslexia, autism, ADHD, ADD and dyspraxia. Our head of internal recruitment, Charlie Waterman, explores why neurodiverse talent shouldn’t be overlooked, and how Data & Analytics specifically can do more to tap into and harness this incredible pool of talent.` Exploring how employers can create a smooth recruitment process, successful onboarding programmes and retention schemes, this article highlights how all of this can be tailored to be accessible for anyone with an invisible disability. To read more on this topic, click here. Computer Weekly: What has a year of homeworking meant for the DPO? Employers in a significant number of industries across the world have had to uproot from the office to working from home because of the COVID-19 pandemic. For many of these employers, it appears that remote working, or a hybrid model of working, will become the norm post-pandemic.  But what has this sudden shift meant for the likes of Data Protection Officers (DPOs)? Most of these professionals have had to get to grips with managing and handling sensitive data from the comfort of their own living room. According to data from IBM, 70 per cent of DPOs believe that the shift to remote working will increase the likelihood of data breaches. So how can DPOs enjoy the benefits and perks of working from home, without the stress of poorly managed or breached data? In this article by Computer Weekly, steps are outlined on how DPOs can work closely with IT teams to minimise any data risk that could happen. This includes: Not allowing DPOs access to everything if it’s not necessaryDiscouraging local storage of dataRegularly reviewing security standards To read the full article, visit the website here.  Solutions Review: The three best Data Engineering books on our reading lists There’s no better feeling than getting stuck into a really good book. Not only can it be a great way to escape the stresses of everyday life, but by continuously absorbing new information, your knowledge on a specific subject can grow immensely.  Any branch of Data & Analytics, but especially Data Engineering, requires employees to always be thinking one step ahead, staying on top of new trends and keeping up to date with specific coding languages. While everyone learns in very different ways, reading is a brilliant education tool. Whether you’re a visual learner, an auditory learner or a reading learner, books and audiobooks could be the key to expanding your knowledge.  Solutions Review provides Data Engineers with three of the best books on the market at the moment to help you keep on top of your professional development. Data Driven Science and Engineering by Brunton and KutzData Engineering with Python by Crickard An introduction to agile Data Engineering by using data vault 2.0 by Graziano To read more about each of these books, click here.  We've loved seeing all the news from Data & Analytics in the past week, it’s 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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