03 Dec 2022
Best Tips To Scale Up Your Data Science Team 2023
Works at Ekeeda
As we are on the edge of 2022, it is now crystal clear that data science concepts are no longer restricted to tech companies but even mid-sized businesses and small enterprises are making optimum use of it. With the vast amounts of data floating around, companies – be it big, medium or large are turning to data and analytics to gain an advantage over their competitors. Data Science is one of the most emerging fields across the globe and it’s the field that is quickly gaining momentum and is highly in demand in the market. You will find the use of data science in nearly all the fields such as multinational corporations, government bodies, e-commerce giants, healthcare, logistics, shipping, etc.
In fact, various small or medium businesses in India are on the hunt for data scientists so that they can elevate their business and take it to the next level. And the good thing – it’s a high-paid career with plenty of growth opportunities. If you’re always attracted to number crunch, mathematics, science, and technology, then this is the field for you. Do many people wonder what jobs they can get with a computer science degree? Which are the jobs that will make you rich? It’s Data Science – the hottest career field for millions of aspirants in India.
Data is getting wilder and wilder and the Data science field continues to get more complex with technological advances. Therefore, data scientists are prestigious professionals in most companies. If a company wants to pull advanced data analysis & best predictions based on its sets, then it will bring resources into its data science strategy. If you study data science and become a certified professional, you’re guaranteed to do challenging yet rewarding work - in terms of growth prospects, salary, job satisfaction, etc. Data science is considered the highest-paid and hottest job of the 21st century. With data being generated in quintillions and reaching wild levels, data transformation is getting harder and harder. Companies are getting grappled with data floods and legacy systems and varied forms of inherited data structures. The cloud is the only way for companies, processes, and businesses to head out from it.
Cloud computing will make it possible to centralize and connect the dots between data sources. It will allow customers to ask better questions that give relevant and advanced solutions, including questions they were not able to ask previously. Cloud also offers better access to new advanced data science tools that will not otherwise be available in the industry. If you want to step into the field of data science, there are a number of ways you can prepare yourself to take on some of the most challenging yet exciting roles. Perhaps most importantly, you will have to impress your senior managers through your expertise and work experience. One such way you can build those skills and experience is by taking up the advanced Ekeeda data science program.
To learn advanced data science concepts, you can enroll with top players like Ekeeda which offers an industry-oriented data science program. This program is designed to develop excellent data science skills that aspirants or working professionals are seeking. The online training program offers students or working professionals with a golden opportunity to participate in experiential learning experiences. It allows aspirants to build hands-on experience prior to graduating. What’s more? You even get industry-relevant training, 1:1 live classes, 100+ assignments and capstones, and placement assistance in top techs and start-ups such as Datascope, Addepto, Appsilon, BCG Gamma, Ugam, Tiger Analytics, Cloudera, Brainvire, IBM, Yalantis, Peerbits, etc.
Here are some data science tips which we’ve combed up to let you scale up your data science team in 2023:
Dark Data Is Very Important
Data explosion is arguably outpacing the ability of businesses how to use it, thereby culminating this into dark data. The information asset companies collect, process, and store during regular business activities but later fail to use it for other purposes. However, if data scientists work on it and brainstorm, it can uncover hidden co-relations between important pieces of information that once thought were unrelated relations between pieces of information that were thought to be unrelated.
Dark data will represent an important regulatory risk in various processes. For instance, bank regulators are not impressed by the presence of existing data that reveals red flags or fraud. But it could have been used to prevent data breaches or fraud. Machine Learning and AI can be used to identify and manage unstructured data, and quick scanning, tag, and classify them for use. It can help analyze vast amounts of data. Especially, ML and AI can easily manage the humongous data volumes to identify potential variances and unleash other hard-to-get insights.
Gone are the days, when the stakeholders and big tech companies had to rely heavily on data science pundits; who would decide the fate of the company. In short, the days of the small handful of data scientists who would run the process or address the entire company’s needs are over. The length and breadth of data challenges today’ call out for teamwork from data science experts. It demands a robust team with strong senior data scientists to prepare for, analyze and operationalize the data issues.
Also, many companies don’t need a lot of data scientists but a way to amplify their impact. Existing data scientists along with new and upcoming talents with cutting-edge skills should divide the focus between micro & macro insights and harness the collective expertise of analysts and business managers.
Become a Master of Data Science by going through this Online Data Science course today!
The inability to easily access the potential data are common worry amongst the data science team and business users. It can impact data processing speeds & lead to rapid shifts or changes in business requirements. Data democratization is often seen as the solution to overcoming it. But while it sounds easy, it requires a fair amount of hard work, strategy, and a planned approach to getting the desired outcomes. It contains balanced availability, privacy, and security.
Data democratization doesn’t mean making all the data readily accessible to everyone, in spite of being trusted, internal team users. A good example would be prescription records of healthcare companies – certain drugs or medicines will only be recommended under specific conditions. To allow general access would be a breach of patient confidentiality. Another instance would be HNI customer data – making it democratize and accessible to everyone means potential leak of valued information amongst commoners and leak to account hacks or fraud transactions. Infact, they won’t be any better way for companies to unlock the value and drive decision-making through potential data other than the cloud concept.
Companies need to drive analytics with a top-down approach if they really want to deliver optimum results. The lower level skilled data scientists will be able to demonstrate clearly that they make decisions not by feeling that pure data facts and figures. To encourage the company to make use of dashboards, the data science head can ask for supporting evidence or data points from dashboards before they provide any form of business recommendation. How can companies gauge their data science needs? From the moment a problem gets identified, how long will it take for stakeholders to gain valuable insights from the data? These questions will be answered through top to down data driving operations.
Data Science is a popular field and nearly every company will integrate data science principles into their daily work and operations. It is no surprise that tech companies – including tech wizards like Google, Accenture, Uber, and IBM – came out on this. The exceptional growth of big data was created due to the internet, which is closely hooked up to software & advanced technology. Data Science really is about processing a lot of information for business elevation and customer satisfaction using various tools and technology.
So will it be worth pursuing a career in data science? Well with so many exciting job roles of data scientists, the answer will be definitely YES! However, finding out which career path in data science suits you, will totally depend on your individual strengths, likes, and dislikes. The Data Science career path in India is simply fascinating and shows no signs of slipping down in the near future in terms of popularity and opportunities. Data Science will continue to shape and influence businesses and companies’ profits and growth.
A Tip - Set a clear Data Science Roadmap that will define the milestones in your career journey. Use the roadmap to track your Data Science Journey, see where you stand in preparation and what is your next move! Once you have considered factors like your personal background, interests, and career aspirations, you can enroll in the data science program and take your next step toward achieving your career goals.
Learn Data Science by taking up Ekeeda Data Science Online Program today!
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