With Big Data ruling over the businesses far and wide, Data Science had become a sure shot pathway to the Digital Revolution that is churning the wheels of the world as we speak. Today, with the advent of the Internet of Things, the number of connected devices around the globe is increasing exponentially. In fact, by 2020 the installed base of IoT devices is predicted to rise to nearly 31 billion globally. More and more companies are now joining the Big Data bandwagon to boost the overall efficiency and functioning of their organizations. People around the world are actively using social media, mobile devices, and other online platforms to accomplish numerous tasks.
According to Cisco, M2M connections will represent almost half (46 percent) of total connected devices by 2020.
All of this is resulting in a drastic increase in the overall data present data. This data is the gold mine of the new era. It holds all the secrets to transforming industries for the better and the change has already begun. Companies across various sectors such as healthcare, business, education, and finance, are leveraging data science technologies to tap into Big Data. Advanced technologies like Artificial Intelligence, Machine Learning, Deep Learning, and Predictive Analytics can efficiently uncover the hidden trends and patterns from massive data sets. However, extracting meaningful insights from data requires skilled and trained data experts who can manage, process, and analyze enormous amounts of data.
New career opportunities in Big Data and Data Science have spurred the demand for online Data Science courses. Aspiring students who wish to build a career in data science can opt for these courses and master data science concepts at their own pace and convenience.
Data Science technologies are rapidly transforming the business sector in the following ways:
Data-Driven Decision Making
According to Forrester almost 38% of businesses find it a challenge to correctly interpret and implement the results of data analytics within their day-to-day functioning. This is where a data scientist could make a difference. Data scientists are essentially data wizards who tread both worlds – IT and business – and hence, they have extensive knowledge on how to deal with large datasets to extract meaningful insights from within them. They have a solid background in Computer Science, Mathematics, and Statistics. Using advanced statistical and predictive tools, data scientists can transform an organization’s data into actionable insights to drive business growth, enhance business decisions, boost sales and revenue, improve employee productivity and efficiency, and much more.
Identify Latest Market Trends and Business Opportunities
One of the fundamental objectives of predictive analytics is to determine and identify valuable patterns within vast data sets. As data scientists and data analysts dive deep into these large data sets, they can uncover useful insights about the latest market and consumer trends and their taste and preference patterns. With such information at their disposal, entrepreneurs and marketers can streamline and restructure their business processes and marketing and sales strategies to best fit the consumer demands. As entrepreneurs begin to understand the pain points of their consumers, they can create better and more innovative products and services.
Another benefit of analytics is that it can help discover new and fresh business opportunities in both existing and emerging markets. Thus, you can rethink your expansion strategy and venture into new markets to gain a more expansive customer base.
Identify The Potential Target Audience
As mentioned in the point above, data analytics helps unravel valuable information about customers and their preferences. By offering you an all-comprehensive view of the market and your customer base, data analytics can help you understand how your customers are interacting and engaging with your brand. Leveraging AI and ML tools, you can get access to customer information such as their age demographic, their location, their buying patterns, their likes and dislikes and so on. Such insights help you identify the audience you need to target and further segregate them into customer segments according to their age, behavior, preferences, etc.
Categorizing your target audience into smaller segments has a clear benefit – you can design personalized messages, emails, offers, and marketing campaigns according to their specific needs so that you can better connect with every customer segment.
One of the greatest advantages of ML is that using ML algorithms we can teach machines to perform certain tasks by themselves. Machines can be trained to ‘learn’ from behavior patterns and cues and perform specific tasks automatically. For instance, the outcome of scoring credit applications or insurance claims is either ‘approved’ or ‘rejected’. This task can be automated easily by performing risk analyses on historical data to determine an applicant’s credit score, credit history, criminal record, etc. Then again, automating emails using tools like MailChimp allows you to customize and send the right message to the right audience at the appropriate time.
Automating such minor tasks not only saves a significant amount of time and effort, but it also allows you to focus on fortifying the other core aspects of your business.
The primary aim of data science is to continually sift through enormous amounts of data to uncover opportunities for innovation. Data scientists are experts in solving complex business problems using advanced ML and statistical tools. They constantly find disruptive ways to find better solutions to old problems. Data scientists along with data analysts and ML engineers continually monitor data to identify groundbreaking opportunities to transform business operations for the better. For instance, Zurich Insurance leveraged AI computing solution to fully automate the handling of injury claims, thereby significantly minimizing the inefficiencies in the process.
As new insights keep surfacing from massive data sets, companies can harness the opportunities of creating new products and services, optimizing their resource allocation strategies, maximizing sales, and so on.
As the name suggests, Data Science is all about studying the science behind the data, and using methods to analyze and interpret data to bring value to the table. It is based upon real patterns and trends hidden within the data. As companies around the world are realizing the potential of data, they are no longer relying on hunches and gut feeling, but instead they can base their decisions on real-time, actionable data insights. In the near future, data science will be a must for every company that wishes to stay relevant in the competitive market scenario.
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