3 challenges faced by data analytics teams

Eoin Pierce our consultant managing the role
Posting date: 5/31/2015 3:47 PM

...And how they affect your career.

We have said it before, and I am sure we will say it again. The industry of data analytics and the associated positions within it are still, in relation to other industries at least, in their infancy. While there have been associated roles such as I.T. focused or predictive analysis based careers for some time. It is only with the advent of large, disparate and often difficult to mesh data sets, that specific roles such as Chief Data Officers (CDO) have risen to prominence. We discussed some of the challenges facing the CDO in a recent article, not the least of these being the integration of silo mentality departments into the larger whole. In this article, we would like to consider the wider issues around data analysis and how you as a front line worker, need to consider them in relation to your career.

Let me be clear, this article is not going to be the 'be all and end all'. It’s more a general musing on the situation than a stone tablet of universal guidelines. For a start, I am sure there could be a lot more on our list of 3 challenges. In fact the list could probably be hundreds of lines long but, for the sake of convenience, let’s just look at three big areas of consideration in the data analytics world.   

Understanding the potential of big data issues. 

As I am sure you are aware ‘Big Data’ has been the Holy Grail buzzword for the last few years. The phrase seemed to go through a distinct cycle of buzzword, keyword, questioning it’s meaning, doubt and finally acceptance that it really means little in isolation. We know what big data is, we probably always have, but the real question lies in its application in real world environments. Clearly the effective data analyst is going to be not only aware of the potential here but be able to see the application and implementation of results in the context of the workplace. A data analyst would probably therefore be well advised to not only understand the big picture but to concentrate their focus on application.

Real-Time Integration. 

The sheer amount of stored data available is one issue, the input of new information is another entirely. If you consider the data flow of even a multi-site retail outlet such as one of the big supermarkets, you begin to realise the importance of immediacy in the analysis of data. This is a key factor in your potential career development. A talented analyst who understands the area of real-time data is likely to be in great demand. In many cases, of course, the result of real-time data may arrive faster than the business can utilise, and this is where integration experts will find themselves very welcome.

Bridging the ‘talk’ divide. 

The reality is that the implementation of results, the use of refined data, and the practical application of your energies is, for the most part, likely to end its cycle with a non-data aware person. Accompanying this, there is, therefore, a language divide. A good, real life desirable skill to acquire is the ability to simplify and practically explain your work. Talk the talk of the user, and you will make many friends in the workplace. Of course, we are oversimplifying here and even being a touch flippant but the message running through all this is simple. The data world is fast changing and difficult. A career in this (or indeed any) industry is often built on not only being an expert, but on being the expert who understands how to fit their industries demands and anticipate new ones.

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Weekly News Digest: 14th - 18th June 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. Gov.uk: Five signs of a good data quality culture Particularly post-pandemic, we all want to know that our data is fit for purpose. In this article from the Government Data Quality Hub, they look at five ways to ensure that your data's quality is right for your's and your users’ needs. This includes: Everyone is involvedData quality is a commitment, not a taskYou know what works for your organisationYou know why quality mattersYou are proactive not reactive We know that committing to a good data quality culture is a continual process. This core advice allows us to take a step back and think about how you can understand your unique challenges and involve the right people, so you can prevent bad quality data before it damages your work. See more on this here. Analytics Insight: 5 types of artificial intelligence that will shape 2021 and beyond We really like this article from Analytics Insight that explores the future of technology, and specifically the rise in uses of artificial intelligence (AI). AI is often seen to be disruptive as there is an assumption that robots could take over and jobs are wiped out, but it’s more likely that humans and machines will work together to streamline processes across a range of industries. The different types of AI to keep an eye on include: Customised technology providerChoosy algorithmHuman-machine interactionReciprocating machinesTheory of mind We’re always excited to learn more about new technologies, click here to read more on this. KD Nuggets: Five types of thinking for a high performing data scientist In this piece KD Nuggets look at how the way our approach to problem-solving may be guided by your personal skills or the type of problem at hand. As a Data Scientist, appreciating different approaches can help you more effectively model data in the business world and communicate your results to the decision-makers. Whether this is model thinking, systems thinking, agent-based thinking, behavioural thinking, or computational thinking, taking the time to understand your approach will significantly help the way you complete the function of your role. To read the full article, see here.  TechRepublic: These 220+ courses will help you master tech skills and prep for IT certification exams We know that there is a digital skills gap. According to Boston Consulting Group, there will be tens of millions of job vacancies by 2030 that will be hard to fill because not enough workers have the required skills, many of which are in technology. One of the best ways to upgrade your skillset is to complete extra training and qualifications to ensure you’re always learning more about your market and providing yourself with the best opportunities to achieve your next career step. ITU Online has over 200 courses covering cloud deployment, cybersecurity and more. Of course, this isn’t the only way in which you can level up your skills, but it’s a good place to start! To read more about this, 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.    

How Will Embracing Flexible Working Help The Life Science Sector To Grow?

COVID-19 has drastically changed ways of working in the Life Science industry. Overnight, teams moved online, while new research had to be prioritised. Life Sciences were already moving towards more remote working, and the pandemic has only quickened this shift. There is no doubt these changes have fundamentally changed the Life Science sector and how professionals working in this space operate post-pandemic.  However, uncertainty still remains about the viability of remote working for the sector and there is a divide between those able to work remotely and those who need to go into ‘wet labs’. Is remote working a step too far for Life Sciences? Collaboration  2020 saw an increase in collaboration between professionals working across different areas of Life Sciences. Interestingly, organisations who may usually compete came together to share data and work towards a shared goal. Collaboration is essential in Life Sciences, yet for many, remote working reduces spontaneous teamwork and creativity.  New flexible lab spaces may be the future for Life Sciences though. RUNLABS have recently opened their first fully equipped flexible lab space in Paris for scientists and companies working in Life Sciences. This space hopes to builds on the existing collaborative approach in the industry and encourage further cooperative innovation. Efficiency  Many employees noticed a spike in employee efficiency when working remotely. By eliminating commutes and increasing flexibility, employees were able to be more productive with their time. Remote working also allowed organisations to streamline processes and reduce time spent in meetings.  However, insight from McKinsey highlights that research and development leaders estimate productivity has fallen by between 25 and 75 per cent due to remote working. Those in pharma manufacturing have reported lower levels off efficiency, as well as the potential for lower-quality outputs.  Research The pandemic forced remote trails to become a necessity, and since then, they have increased in popularity. While face-to-face research is still preferrable, remote trials can reduce costs and improve efficiencies. Indeed, on-site monitoring accounts for a significant portion of the costs of bringing a new product to market, yet this is no longer necessary in remote trials.   Not only are remote trials more cost-effective, but they can open research to a wider range of patients and can increase the communication between trial participants. Diversity Flexible working can run a risk to diversity and inclusion though. McKinsey also notes that, ‘when faced with a crisis, leaders often revert to relying on the core team of people they already know and trust. This disproportionately affects women and minorities because they are often not part of that group. Differences in perceptions and experiences of inclusion results in individuals or communities being disenfranchised, which can be devastating to careers and create a two-tiered culture.’ We know that 27 per cent of D&I leaders say their organisation have put all or most of their initiatives that embrace diversity and inclusion on hold because of the pandemic. However, remote work unlocks new hire pools and opens up the workplace to a more diverse workforce. Workers are no longer restricted by their geographical location or personal circumstances. Flexible working is an opportunity for Life Science organisations to harness a wider talent pool and increase their diversity. There is no doubt that Life Science is one of the most cutting-edge sectors globally and the pandemic has only cemented this. COVID-19 has shown the potential for remote working in life sciences, and in-person health care professional access may never return to pre-lockdown levels. But, going forward life sciences need to remember remote working is not practical for everyone nor every role. Organisations will need to consider individual wellbeing and role efficiency as they decide their next step.  If you’re in the world of Data & Analytics and looking to take a step up or find the next member of your team, we can help. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more. 

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