How Data Analytics Professionals Should Create A Long-Term Strategy For A Successful Career

Data Analytics is the hottest, in-demand job and demand for this role will further increase by over 30% in the next two years. Given how this field is ever-evolving, Data Analytics professionals need to keep track of the latest trends in the analytics landscape and upskill for delivering values. Consequently, to thrive in their profession, Data Analytics professionals should devise their career path and execute on it.

Strategic Approach To Career-Building

Developing vertical-specific skills such as:

1. Data gathering
2. Data wrangling
3. Descriptive and inferential statistics
4. Data visualisation
5. Data intuition

In the ever-changing analytics marketplace, data analytics professionals should have the aforementioned skills to analyse data and deliver meaningful outcomes. Gathering data often involves screen scraping as professionals do not always get off-the-shelf data. To carry out screen scraping, analytics professionals should have an understanding of HTML and JSON structures to request data programmatically from websites. After collecting the data, they need to be aware of the best practices of cleaning the data and improve its quality for further processing. After preprocessing the data, professionals utilise descriptive and inferential statistics to unearth insights into data. Further, data visualisation artistry assists in exploratory data analysis and presenting insights into visual form. This is where data intuition comes to play; after exploring the data, analytics professionals acumen to mould the data using algebra and provide important insights. Programming and statistics are at the core of unveiling insights into a plethora of data, analytics professionals should continuously brush up their coding skills by participating in different quizzes and attain problem-solving skills. While these practices will help them to improve their ability, it may empower them to optimise their code to increase the efficiency of algorithms. Along with constantly learning, the ability to apply intellect for solving business challenges is vital for any professional. However, most of the data analytics professionals struggle to implement their learning in order to crack challenges that business posses are one of the longest standing predicaments. Therefore, to mitigate such problems, data analytics professionals should engage in several hackathons.

Hackathons and contribution to hosting platforms

Hackathons not only facilitates a learning environment to obtain new technical skills but also provides them with a platform for competing among various data analytics professionals. In addition, hackathons are a perfect place to network with like-minded people for sharing ideas pertaining to analytics and assimilating different perspective. This increases the chance of collaborating with professionals to work together on projects that are of common interests, and in turn, expediting the data analysis process. Further, contributing to open-source projects hosted on GitHub and competing in Kaggle’s competitions exposes data analytics professionals to various real-life challenges while exploring data for insights. Contributing to these demonstrates their capabilities in solving business challenges, which can help them in gaining recognition from recruiters.  Technical content writing is now becoming one of the quickest ways to express yourself online. With noted portals looking for fresh takes on sought-after topics related to artificial intelligence, machine learning, data science and IoT, among others, more and more people are choosing this route to express themselves online.

Attending developer summits and seminars

Moreover, attending conferences such as Analytics India Magazine’s Machine Learning Developer Summit and other similar convocations and seminars will assist in obtaining new ideas and the latest trends. Collectively, the knowledge and skill-set that data analytics professionals obtain from hackathons and developer submits can also allow possessing cognitive thinking. This might empower professionals to manage bias and variance tradeoff effectively, and in turn, improve the accuracy of machine learning models.

Relevance of communication skills and socialising 

Along with gaining technical skills and participating in developer submits, an analytics professional should obtain communication skills for effectively translating the technical findings to different audiences. Conveying the insights into data adequately through reports, visualisations, and more is as important as utilising best practices to process data for an in-depth analysis. Without an appropriate way of communicating, insights from the data can be bootless as it may not persuade the audience. Besides, effective communication also assists data analytics professionals in showcasing their ability in technical skills. Building social capital through engaging in social groups is another crucial aspect of strategising career success for data analytics professionals. Networking helps in accomplishing contacts that can be purposeful in getting recommendations, and in turn, better job opportunities. Moreover, networking can get referrals to different recruiters to make the next career move.

Outlook

Apart from performing aforementioned practices for a successful career, data analytics professionals should be passionate enough for blazing their trail to go above and beyond what they have learnt and solve critical business problems. Coming up with new developments in analytics can place data analytics professionals in a way that can separate them from their competitors. To attain this, they should regularly try to enhance their skills through all possible means and be the frontrunner in the analytics landscape.