Why I Decided to Write this Article?
I wanted to take some time to write an article for those of you who are interested in data analytics but you’re hesitant to start. A common concern about starting something new is to worry about the future of that thing, in this case the future of data analytics. I have been teaching data science topics (programming and statistics) for quite a few years. Data Science is the umbrella term for a number of fields that use methods, processes, algorithms and systems to gain insights from data. Data Analytics is one of those fields. By pure accident, I ended up learning and teaching SAS programming and SAS dominates the analytics space, in particular advanced analytics. SAS Institute. hold about 1/3 of the market with their different software solutions. So, in this article I want to explain what data science is in more detail and then explain to you how I see the future of data analytics.
What is Data Science?
Data science is the multifaceted approach of extracting actionable and meaningful data from a vast collection of structured or unstructured data by employing several modern methods, processes, algorithms, and artificial intelligence techniques to assist in the decision-making process. It includes cleansing, aggregating, and preparing data for analysis and processing, developing algorithms, analytics, and AI models, finding patterns, and finally presenting the results to reveal those patterns. Lastly, it employs different software to translate the patterns into predictions to facilitate businesses in making informed decisions.
Skills of a Data Scientist
To become a data scientist requires high skill, since data scientists are at the top of the hierarchy. As a result, they are required to be skilled in mathematics, statistics, advanced computing, modelling, analytics, and visualization for extracting the most vital and relevant data from muddled masses of information and help promote efficiency and innovation. They are also experts in the use of software and programs such as Java, Hadoop, SQL, Python, and Pig. Finally, they depend heavily on different subfields of artificial intelligence including machine learning, deep learning, and the internet of things.
Scope of Data Science
Data scientists can be employed in diverse disciplines such as:
- detection of anomaly (disease, crime, or fraud)
- automation (background checks)
- decision-making and classification (such as classifying emails as junks or important)
- forecasting (sales, revenue, customer retention)
- pattern detection (weather patterns, financial market patterns)
- recognition (facial voice or text)
- recommendations (based on learned preferences recommendation engines may refer to movies, restaurants, or books you may like)
Large-scale digitalization at the global level is leading to high-end demand for data scientists. IBM Predictions reported that there would be a 28% increase in the demand for data scientists in 2020 and the estimated figure of data science jobs is 2,720,000 in 2021.
So, career options in data science are numerous. Consequently, some of the job titles include: business intelligence developer, data architect, database administrator, data engineer, data analyst, big data analyst, machine learning engineer, statistician, and business analyst. As businesses are utilizing more and more data-driven technologies and programs for decision-making, the demand for highly professional data scientists is increasing. According to Labor Statistics of the United States, data science employment is estimated to grow by 20% by 2026. For instance, the healthcare sector is in demand of data engineers to help in constructing automated systems for the analysis of complex data in clinical applications. By 2021, the healthcare sector will generate 20,000 jobs.
Reasons for pursuing a career in data science and its related fields:
- In-demand profession
- Opportunities of working with popular brands and organizations
- Become a domain expert
- Become a freelance consultant
- Teach data science online or in person
- Join data competitions and win money
- Become a data scientist
Next, let’s discuss the three subtypes of data science namely Data analytics, business analytics, and machine learning:
Data Analytics and the Future of Data Analytics
If you are interested in the technical aspects of data, you should consider data analytics. Data Analytics is about examining and analyzing raw data to find out trends or patterns and draw conclusions based on the information they contain. Data analytics assists businesses to boost profits, optimize operational efficiency, promote marketing campaigns, improve customer service efforts, and get a competitive edge over rival companies. The following figure describes the salary of a senior data analyst (Glassdoor, Inc., 2021).
Digitalization of Data
Digitalization of data is driving the companies and organizations to go for the data analysts who can define big data, discover patterns, spot opportunities, and generate insights for boosting up the businesses. The PWC estimated 2.7 million new jobs in data analytics for 2020 (PwC , 2020). Popular brand software such as AG, Oracle Corporation, IBM, Microsoft, SAP, have invested 15 billion USD in software firms that specialize in data management analytics. The result of this has been an increase in demand for information management analysts in multiple industries and sectors.
Future of Data Analytics and Demand
the future of data analytics is very favorable. Data analytics is considered one of the most in-demand expertise by 75% of internet of things providers and 68% of the providers are struggling to find employees with relevant expertise. (Columbus, 2017). Prescriptive, descriptive, diagnostic, and predictive analytics are the three major sub-fields of data analytics for pursuing a career in data science. The best paying data analyst jobs in 5 US cities as of 2020 are shown below. Certainly, pay is of course not only about location, as a big data analyst salary will be greater than your regular data analyst salary because larger companies (companies that have big data!) will be hiring you.
A distinction between data and business analytics is not necessarily common as data analytics typically encompasses business analytics. But it can be helpful to make a distinction for people who are new to the world of data related careers. Business analytics is the combination of skills, technologies, and practices that enables continuous iterative exploration and investigation of past business performance to gain insight and drive business planning (Chintan, 2009).
Data Analytics vs. Business Analytics
BA is similar to data analytics, with the difference being that with BA, the implications are directly tied to the health of the business or improvement of business metrics. For example, financial modelling to figure out how a project or asset is doing is a common task. It is useful to consider that someone in this position uses data but treats data as a means to an end. On the other hand, data analytics is a more general term that includes activities that may not initially or ever have direct business implications. For instance, the US Department of Agriculture work with data to keep the public safe (i.e., supporting water movement in soil) yet those activities are clearly not about ensuring viability of the Department.
Dealing with big data has become a particular challenge. Big Data refers to the Volume, Variety, and Velocity of data that a company has to deal with.
Career Paths in Big Data Analytics
A degree in the field can open new avenues for graduates in the light of the widening talent gap that is increasing due to the challenging nature of big data. Marketing Week report ‘the Future Marketing Organization’ revealed that 24% of marketers rank the data skills as their biggest perceived skill gap. According to a survey, the estimated job growth for management analysts is 14 % until 2026. Moreover, the market research analysts are going to receive an employment growth of 23% by 2026.
In 2017, three out of 5 top five technical jobs were related to data analytics in the US. In addition, that included a median salary of USD 122,000 for data architects, big data analyst salary of about USD 115,000, and data engineers had a median salary of USD 105,000. The comparison shows the monetary aspects of pursuing a data analytics career. (Dataversity, 2017).
The above-mentioned table shows the statistics for the big data analytics skills in IT jobs that were advertised in UK, 2016.
According to a ‘Peer Research-Big Data Analytics Survey’, the future of data analytics is a future of major demand. Big data analytics is a topmost priority or a priority for about 90% of organizations to improve their business performance.
A survey by Deloitte revealed that 62% of their respondents were employing some form of analytics for assisting in their business needs. The figure below exhibits their beliefs and inclinations towards using analytics in business.
According to the ‘Analytics Advantage’ survey, 96% of respondents reveal that analytics is going to become an essential part of their organizations in the next three years. Around 49% of respondents believe that analytics is the key ingredient for better decision-making for organizations. The following figure shows this.
The above-mentioned survey also revealed that there is a growth in structured and unstructured data. Around 84% of respondents admitted that their organizations are using data analytics to process unstructured data in the form of weblogs, e-mail, photos, and videos from social media.
Machine learning simply refers to an approach to data analysis that automates analytical model building. It is a subtype of artificial intelligence and is based on the principle that systems can learn from data, point out the patterns and make decisions with minimal human intervention. It helps automatically create models that can analyze bigger and complex data, deliver faster and more accurate predictions and results. It gives an organization a better chance of identifying profitable opportunities and avoiding potential risks.
Market research reveals that the global machine learning market was 7.3 billion USD in 2020 and is expected to expand to $30.6B by 2024 (Forbes , 2020). Gartner predicts that more than 80% of projects of IoT will be using AI and ML by 2022 (Kaur, 2021).
Reinfinitiv’s 2020 AI/ML report revealed increased use of unstructured data with 17% of firms employing this type of data, which was just 2% in 2018.
Comparison of salaries
A big data analyst salary will range from about $100,000 USD to $120,000USD, the average salary of a market research analyst is 63,120 USD, the average salary of a data scientist is 88,779 USD, the average salary of a data architect is 116,710 USD, and the average salary of data analysts 60,208 USD, according to IE University (VIVAS, 2021).
Columbus, L. (2017, August 21). Big Data & Analytics Is The Most Wanted Expertise By 75% Of IoT Providers. Retrieved from Forbes: https://www.forbes.com
Chintan, Bhatt. (2009-06-18). “BUSINESS ANALYTICS-Applications and Practices”. CSI Communications. Retrieved 2009-06-20.
Dataversity. (2017). Big Data Analytics . Retrieved from Dataversity: https://www.dataversity.net/
Glassdoor, Inc. (2021, March 27). Senior Data Analyst Salaries. Retrieved from Glassdoor: https://www.glassdoor.com/
Kaur, H. (2021, Jan 19). Top 5 Machine Learning Trends For 2021. Retrieved from GeeksforGeeks: https://www.geeksforgeeks.org/
PwC . (2020). Technology, Data & Analytics. Retrieved from PwC : https://www.dataversity.net/20-reasons-big-data-analytics-best-career-move/#
VIVAS, G. (2021). BUSINESS ANALYTICS & BIG DATA. Retrieved from i.e. School of Human Sciences and Technology: https://www.ie.edu/