Data Science is the hot topic since the information age started sweeping the world with its digitalization and so, we keep hearing the title “Data Scientist” almost every other day. According to popular “The New York Times”, Data Science might steer a greatest revolution in almost all the areas of industries ranging from business to government, health care to academia and more. Based on the number of career opportunities, Glassdoor has ranked data scientist as the #1 “Best Job in America” for the year 2017.
So, how does data science claimed this title “the sexiest job of the 21st century” pretty soon?
With high business competition, organizations have realized the power of big data and harnessing it to actionable insights. Remember, big data is here to revolutionize however without the expertise, who can leverage the data using cutting-edge technologies, big data is not going to hit the headlines. This is where our modern day heroes, “Data Scientists, “Data analysts, Big data specialists steps into the spotlight.
Why do We Need Data Science?
Think about the days before the Data Science revolution started, the data are small and structured in size which can be measured by using simple BI tools. But today, with the development of technology, the data is pouring from almost all the places like financial logs, multimedia forms, text files, sensors, and instruments. The most challenging part in this is, they are mostly unstructured or semi-structured. When we look at this growth graph, the year 2020 will have more than 80 % of the data to be unstructured.
So, what are we going to do to study this big unstructured mess??
Simple BI tools are not going to do the job for you as they are not designed to process huge volume and variety of data. We need advanced analytical tools and algorithms to not only process these data but also analyze them to extract meaningful insights for the business.
Let’s dig deeper to see how Data Science can be used to extremely helpful to us.
- Over the years, we have seen many natural calamities that have brought in a devastating loss to us by swallowing many precious lives. What would have been the situation, if it has been predicted well in advance of such occurrence? This predictive analysis of weather forecasting is an example of Data Science. The data can be collected from ships, radars, satellites, aircraft and used to analyze and build models. These models can do accurate weather forecast and also predicts the occurrence of natural calamities.
- The most renowned example which is often quoted when we talk about Data Science is “Self-driving” car. This car is built after analyzing the data collected from sensors, cameras, radars, and lasers to create a map of its surroundings. These data will be really helpful in making decisions of when to speed up, when to overtake, and when to stop so that the car is readily grooming without any actual person driving it.
- In the highly volatile business world, the business owners are often looking for ways to create a better customer experience than their competitors. When your customer is looking for a product on the webpage, if precise product recommendations are made then it brings more business to the organization. With the existing data like the customer’s past browsing history, purchase and interests, one can train models to make recommendations for the customers effectively.
These are just a handful of examples but Data Science’s benefits are like the ocean and we need trained professionals to explore the data and bring out the benefits.
What is the Work of a Data Scientist?
A curious kid, who keeps asking “why?” will always think out of the box for his problems. Data scientists are similar to that curious kid, and they keep asking why to dwell upon and bring out the real strength of big data lying silently underneath.
Data scientists are not doing the job of statistician, engineer or an analyst but a little bit of everything and of course, this very essence differs according to the company that you choose to work with. The term Data scientist is a broader term that encompasses different flavors of work. Though the actual work differs according to the company, the general tasks of a Data Scientist include
Task #1: Data Cleaning:
We are aware of the fact that data is pouring from all the corners and there are piles and piles of it being stacked in a not so easy to use format. A Data scientist’s work is to format this data and make sure that it obeys to some set of rules so that it is easy to work upon.
Task #2: Data Analysis:
Data Analysis is not a simple spreadsheet program but typically working with data sets that are too large to accommodate even an excel sheet, and sometimes it may be too large to open in a single computer. Data scientists create plots in an attempt to understand these data and a story is crafted to explain the data clearly.
Task #3: Modeling /Statistics:
In this stage, a deep theoretical knowledge creeps into data science to make predictions. Furthermore, Machine learning algorithms are used to produce good results. The resulting models are tweaked and evaluated to bring out new features that can reshape them to better models.
Task #4: Engineering/prototyping:
Successfully building good models for predicting is indeed great but there is one disadvantage existing here. Only Data scientists can understand these models. So it is essential that these models should be delivered in a presentable visualization forms such as a chart, an application or a metric on a dashboard so that people who aren’t data scientists can also understand them.
How can Data Scientists Add Value to the Business?
Data Scientists are a great data jugglers. With their training in statistics, math, and computer science, huge benefits can be reaped that can contribute immense value to the modern business.
- Data Scientists facilitates the improved decision-making of an organization by analyzing their data. Over a period, with their experience in hand, they can even turn into a trusted advisor and strategic partner to the management.
- Data scientists keep examining their organization’s data continuously and come up with ways to help in better customer engagement and retention, which ultimately increases profit.
- One of the responsibilities of Data scientists is to make the employees understand the organization’s analytics product and help them to adapt to the best practices.
- Data Scientists can create models using the underlying data that stimulate a variety of actions to bring the best business outcomes.
- After analyzing the data, their job is to continuously and constantly improve the value by questioning the existing processes and assumptions. In addition to developing additional methods and analytical algorithms.
- Making certain crucial decisions and implementing those changes is indeed their job. However, One of the vital element includes measuring the critical metrics involved in those changes.
- The essence of data science lies in its ability to pick existing non useful data and combining it with other data points to generate useful insights that an organization can utilize to learn more about its customers and audience.
- Finding the best fit for the job is always a challenging and time-consuming task for organizations. With the help of data scientists and the information available through social media, corporate databases, and job search websites, they can help to find the candidates who can be the best fit the organization’s needs.
Data Scientists add value to any business since they are highly skilled and motivated to solve the most complex Business problems. With a large chunk of raw data, they explore opportunities to derive at information that can help to make critical business decisions. Soon, the way we used to look at the world will change entirely with the power of data that is being harnessed byData Scientists.
Time to Leap into Data Science Career with DataMites™:
The demand for data scientists is increasing each day exponentially. By the year 2020, there will be a requirement of 4 million to 5 million jobs in the United States alone for data analysis skills, but the sad truth is that there is expected a gap of 50% in the resources versus its demand.
It is the best time to indulge yourself in Data Science career and take up certification to steer your career path to the correct direction. DataMites™, one of the leading global professional training providers is training aspiring candidates in the necessary skills they need to work on complex data and apply what they learn toward the benefit of their organization. Those candidates who are joining our Data Science course will receive hands-on training that prepares them to visualize and analyze the extensive set of data and interpret them. You will also gain the required skills to work at big organizations and leverage vast amounts of data to gain useful insights and make decisions.
It is the best time for you to get on board with DataMites™ and join the long list of candidates who have successfully excelled in Data Science career. For more details, please visit https://datamites.com/