Top 5 trends of data analytics to look out for in 2020
The growing influence of data sciences on everyday business operations has been groundbreaking. Data analytics and digital transformation have changed how data has been analysed and utilised. New trends and emerging technologies have made data analysis more efficient with each passing year.
Data analysis is not only instrumental in understanding the performance of businesses but also in understanding the history of a business and for forecasting the future of a particular market. This has proven to be a crucial asset for organizations all over the world.
In this blog, you will get a detailed summary of the up-and-coming developments in data analytics and how it will influence businesses and their functions. Read this blog to find out about the top trends of data science and how you can capitalize on them.
Top 5 trends of data analytics in 2020
- Industry-specific job roles: While specialized roles have always been a part of data analytics, the year 2020 will see an increase in industry-specific roles.. Employers are not only looking for professionals with experience in data analytics but also with extensive industry-specific knowledge. For instance, a data science professional employed in the manufacturing industry should be well-versed in the nature of the data they are dealing with. With more and more industries shifting towards a digital service-dependent structure, industry-specific jobs are likely to increase in number.
- Fast-spreading data governance: The introduction of GDPR worldwide has increased the need for professionals to be skilled in data security and privacy, urging more students to acquire this qualification. These guidelines have not only had a widespread impact on data security, data processing and consumer profiling, but also on the present and future operations of an organization. Data analysts and scientists can come to the rescue of organizations as they can help ensure that all company operations comply with the set regulations.
- Adding machine learning to your CV: Gone are the days when being good at data analysis tools were enough to score a well-paying job in the industry. Today, employers are looking for professionals with expertise in not only data science, but also machine learning technology. The rise of machine learning as a useful asset has driven organizations towards the automation of processes. The upside of machine learning’s increased dominance is that firms can now extract detailed insights which might not be possible for human talent to obtain. However, this would also mean that employment in this sector would decrease unless professionals were well-versed in machine learning technology. Hence, it is essential that, apart from acquiring skills pertaining to data analytics, students also add machine learning to their skillset.
- Experience in fundamental concepts of business intelligence (BI): Business intelligence is becoming a core part of data analytics. With the growing popularity of business intelligence within the business foray, businesses have witnessed great potential in the technology. BI allows professionals to easily interpret complex data and articulate their findings to non-technical professionals. For professionals in the data science industry, adding the use of business intelligence strategies and technologies to their CVs can prove to be beneficial on the employment front. While BI is primarily about effective communication of useful information, professionals must also be well-versed in programming languages, have experience in specific tools and inculcate a problem-solving approach in their work life.
- IoT integrated with data analytics: Internet of Things (IoT) has proven to be a dynamic phenomenon. 2020 will see a bustle of IoT devices (estimated at 20 billion), which will give way to more devices available for data analysis. As IoT devices are finding their way into large corporations, supporting technology to facilitate data analysis is also being incorporated. This will increase the dependency of organizations on IoT devices, resulting in the extraction of relevant and transparent data. Another significant impact that the introduction of IoT devices will have is the generation of more data science jobs, widening the career scope for data analytics graduates.
Data science has started a revolution in the business world that is not only changing how data is handled but also how businesses function. More organizations are using data analytics as a central function and the employment sector is booming with opportunities. This has emphasized the need for skilled professionals who have experience in varied aspects of this industry. The data analytics industry is growing at a rapid pace and the industry is only going to grow bigger, hereon.
If you are looking forward to forging a career in data analytics, you can pursue the Diploma in Data Analytics Co-op program offered by the Toronto School of Management. This program can help you acquire in-depth knowledge pertaining to the key components of data analytics and ensure you learn the necessary skills to take on this ever-evolving industry. Sign up for the course today!