Data science is one of the hottest topics in the industry, so does its application. Data is among the most valuable assets for any company, which can help them to exceed their own growth records. Data science talks about real algorithms. This might sound like fiction to those unaware of it, but in reality, data science plays a huge role in making a business decision.
Why is Data Science a booming industry?
The world is getting more and more digital, which directly implies the presence of a huge amount of data. As per the reports, 90% of the data in the world is generated in the last 2 years only, exponential growth of the data science industry is due to the increasing amount of data being generated. The amount of data that is being produced every day is truly mind-boggling. At the current pace, 2.5 quintillion bytes of data are created every day.
These digital footprints are the most essential fuel for companies to exploit and reach at the top of the ladder. This very well complies with the statement given by Himanshu, co-founder of TechEela that “Data is the hidden power of a company”. To harness this power is the challenge given to the data scientist. Modern organizations use Big data to increase their productivity, profitability, efficiency and reduce cost by using the BI (Business Intelligence) gained from processing this data.
Industry Application
The solution of this challenge begins with the understanding of the business problem and then building a suitable data analytics strategy for it, the subsets of the Data strategy. These processes are applicable to all irrespective of the industry, though the details may vary. These processes are time taking but pay off exponentially with time. Here are few quick things which you should remember in data strategy:
- Data analytics and strategy should be built around the overall business strategy goals.
- Your data strategy should have buy-in from all the departments.
- Data usage should be as per the GDPR and other regulatory mandates.
- Data governance and security should not be compromised.
- Data strategy should also be revised with time.
This challenge begins with understanding the business problem and then building a suitable data analytics strategy which is the subsets of the Data strategy. These processes apply to all, irrespective of the industry, though the details may vary. These processes are time taking but pay off exponentially with time. Here are few quick things which you should remember in data strategy:
- Data analytics and strategy should be built around the overall business strategy goals.
- Your data strategy should have buy-in from all the departments.
- Data usage should be as per the GDPR and other regulatory mandates.
- Data governance and security should not be compromised.
- Data strategy needs to revise with time.
As per Harvard Business Review, Data scientist is the sexiest job for 21st Century. It is almost impossible to see a data scientist post not present in any highest-paying job list. So this trend also indicates the high return on investment; otherwise, why would anyone invest so much. Let’s see how data science is used in the various industries:
- Banking & Finance: use predictive analysis to know the potential customers to assign the proper resources, fraud detection, risk analysis, algorithmic trading, customer retention, etc.
- Marketing: The marketing industry has seen a huge impact from the data science revolution. Inclusive of search engines, consumer behavior analysis for ads, using predictive analytics for Email marketing, social media marketing, etc.
- E-commerce: companies use trends and predictive analytics to optimize the time and route for optimal delivery. Managing the supply and in-house staff based on the trends of geographical location.
- Technology: Be it smartphones, smart wearables, digital assistants, self-driving cars, and many others, they all rely heavily on data science.
These are some of the top industries that are using data science. There are many others like health care, manufacturing, telecom, travel & hospitality, and so on that are seen using data science massively.
To conclude, data science is imperative to survive in the competitive world, and data analytics helps the business heads decide on every important business decision.