Data Science and Analytics: The Emerging Opportunities and Trends To Deal With Disruptive Change

Data Science and Analytics: The Emerging Opportunities and Trends To Deal With Disruptive Change | General | Emeritus

Top 5 data science trends that are revolutionizing business operations in a rapidly changing economy and opening up new career prospects.

What do Amazon, BuzzFeed, and Spotify have in common? They’re all three successful, data-driven, and data reliant. “Customers also liked” to “Which Harry Potter character are you?” to “Discover Weekly”, all of these are a result of robust data science technology and data scientists. Globally, industries have first-hand seen what leveraging data science technology can do for their businesses. Data-driven decision-making enables organizations to respond to consumer trends, offers businesses growth opportunities, and equips them to predict and tackle challenges in a disruptive economy. 

Almost every business today receives large volumes of data that seem overwhelming and chaotic. This is the very same data that builds rich customer experiences, simplifies business decisions, and creates innovations that enrich lives across industries. However, in isolation, data is just that – a bunch of rows and columns with hidden insights.  

In the light of data challenges facing enterprises, we’ve summarized a few data science trends as well as prospects for data scientists. 

  1. Enterprises choose data science as a core business function 

Several companies and their leaders are identifying the value of big data. Businesses are investing heavily in AI and ML technologies to capture more data and capitalize on it. Organizations are investing in data scientists as well to harness those crucial insights for their businesses.

 “76% percent of businesses plan on increasing investment in analytics capabilities over the next two years”

However, around 60% of data within an enterprise goes unused for analytics. Unlocking the power of big data is pushing organizations to shift data analytics to a core function led by Chief Data Officers (CDO). CDOs are expected to work closely with CEOs on holistic data strategies to deliver insights that help navigate disruptions.


  1. Data Scientists and Chief Data Officers are in demand across industries

The average growth rate for all occupations is 8%, whereas data scientist roles are expected to grow by 27% by 2030.

A quick glimpse through Glassdoor shows that a data scientist job ranks second in the list of 50 Best Jobs in America for 2021, with an average base salary of $113,736 per year.

Employers are expecting data scientists to be skilled in tools and platforms of AI, ML, and IoT. They’re expecting expert programmers that double up as coders, who can analyze vast data, drive insights out of each data pattern that enables quick decisions across the organization. Data scientists must adapt quickly, learn skills on the job and constantly adapt.


  1. Employers need skilled data scientists, not just data analysts 

Navigating big data requires a curious mind, a passion for analyzing data patterns, and the ability to predict and derive actionable insights. Businesses today require data science professionals who are technical specialists and can communicate business strategy across functions in an enterprise. While there are learning institutions that offer degrees in data science and analytics, professionals need to be agile to changing business environments. Data Scientists will need to engage in lifelong learning to keep up with the digital transformation, the complexity, and volumes of data that continue to emerge. Data science professionals that upskill and reskill their abilities through their career will find an accelerated path to senior roles in organizations. Emeritus offers mid-level and senior-level professionals high-quality online programs from reputed global universities that enable them to compete in this data-driven economy.

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  1. CDOs will spearhead a data-driven culture across the enterprise.

The 2021 Gartner Board of Directors survey found that 69% of boards of directors have accelerated their digital business initiatives in response to COVID-19 disruption. 78% of respondents believed that analytics would emerge as the top game-changing technology from the pandemic. Businesses are rapidly going digital with new technology, tools, and employees are thrust right in the center of it all. CDOs need to lead this digital transformation in the organization. 57% of senior Fortune 1000 business and technology decision-makers confirmed the appointment of a chief data officer in 2020. Right from upskilling the existent workforce to encouraging the adoption of new data platforms to acclimatize the enterprise to the power of data technologies, the CDOs have a challenging task ahead. CDOs must effectively communicate business strategy, facilitate smooth data governance and advise business leaders on how to create data-driven organizations. 


  1. Enhanced Customer Experiences via data-driven technologies 

Now more than ever, customers are comfortable with digital interactions and are forthcoming with data. Customers are expecting businesses to create personalized services and experiences for them. Whether it’s chatting with the AI chatbots to customer support calls to the team, one-touch access to all customer data and buying patterns is crucial to the business. Businesses need to tie together the various channels of customer communication into one clean and holistic data point. Technologies like Datafabric offer huge organizations that have large volumes of big data to seamlessly integrate different data sources. Data fabric reduces the time for integration design by 30%, deployment by 30%, and maintenance by 70%. Enabling technologies like data fabric in the business gives the whole enterprise access to customer insights. Various departments, products, and services in your organization then work towards creating personalized customer experiences. Going forward, one of the focuses for data scientists is going to be ‘How can our business deliver customized experiences to retain each customer?’ Analysts would need to develop strategies to transform customer experiences by harnessing data insights. Data scientists will work closely with departments across the organization to advise product managers on new product features, enhanced UX/UI on digital platforms, or even improvement in processes for customers. 

Practically every industry today benefits from data science and analytics. While some large businesses leverage the power of data at a macro level to support bottom-line growth, data analytics also equips other businesses with actionable strategies to tackle future challenges in a data-driven economy.

To learn Data Science and Analytics, visit our program page.

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