Data analytics has already got momentum and going forward it will be the core of countless new technology solutions.
It is being increasingly leveraged by startups, small businesses, and large enterprises to improve customer experience, reduce cost and make existing processes faster.
Data is the new fuel and AI is the accelerator! Though even if you have all the data/information still you can’t do much without data analytics. There is no future without data analytics.
As cloud technology emerges, data analytics becomes more popular due to its accessibility, speed and insights you can fetch with no time. Most of the companies are already using cloud technology and the rest are also at least preparing to move everything in the cloud.
Looking at the overall picture it is self explanatory that why you should learn data analytics now. Though here are top 5 reasons why to learn data analytics.
High Demand
Data is the future and this is known to everyone including existing, upcoming companies, entrepreneurs, leaders. Even normal people also want to see the analytics for their personal finances, expenses, daily activities, food calories, etc. That’s the strongest indicator that the demand is very high.
Data analytics is not tagged to a very specific industry or field. It is wide open as a sea. You’re maybe in IT, healthcare, finance, consumer, telecom, or any other business, there is a need for data analytics everywhere.
Almost everyone wants to stop guesswork and be more reliant on data driven decisions rather than luck hence it is more popular and high in demand. That’s the number one reason why you should start learning data analytics before it is too late.
Problem Solving Skills
Building dashboards by applying business logic, updating and inserting data, maintaining data, etc are not a simple job. It requires logical and critical thinking, and it can be built over a period of time when you start learning and working on data analytics.
After working for months or years on data analytics you will start observing changes within yourself. Your problem solving skill gets increased over a period of time. You build your thinking process in such a way that you consider multiple factors, possibilities, and risks before taking any decision.
It does help you in day to day life. You’ll start thinking in a different way, and start
making smarter decisions compared to prior decisions. It would be more driven by data, rigorous research, and calculative risk. You can learn data analytics to improve problem solving skills and make your life even better.
Analytics Is Everywhere
Analytics is the key. One simple example, just look at your mobile where it shows how much time you spent on each individual app. You won’t be surprised if it shows your social media usages 1-2 hours per day. If you think you’re spending too much time on social media then immediately you can make a decision and stop using social media more often.
Analytics is everywhere. You can open almost any application, website, or use any device, you’ll find analytical dashboards. With the help of analytics you create seamless user experience, show suggestions, predict futurist movement, display important insights, and so on!
There is no specific industry that uses analytics. Almost all the industries are leveraging data analytics in one way or another. Data is everywhere, so is data analytics.
Driving Force For Business
Businesses and entrepreneurs become smarter than ever, hence naturally they avoid making decisions based on guesswork. They just want to listen to the data.
Any small changes in the app or a website are driven by data analytics which might have shown some meaningful insights that have triggered these changes. People love taking bold decisions that are backed by some meaningful insights and it can be easily fetched through analytics.
If the analytics show something but you can’t see it with your open eyes. You can always validate looking backward and comparing analytical indicators with the current situation. You’ll find the similarities or some kind of signal that has shown you more likely what’s going to happen in the future.
Businesses are striving to make data driven decisions and you can help them by learning and building your career in data analytics.
Upskill Your Tech Career
Assuming, you’ve already chosen your career path and it can be in tech or non-tech fields. In today’s rapidly changing world, technology is also changing rapidly. Upskilling is not a choice anymore, it is the need of the time.
The technology you learned or started working five years back may have already become absolute or about to become absolute.
There is an upgrade almost every month or two in all the technology that exists today and also tons of new tech is emerging every year. As the time passes you have to see what is latest and you should start learning it.
Data analytics could be the best choice if you want to upskill your tech career or make a switch from non-tech to technology domain. You must try data analytics at least it’s worth giving it a shot.
Data analytics can open many doors for you. There are many job titles to choose from once you learn data analytics:
- Big Data Engineer
- Data Analyst
- Sales Analyst
- Financial Analyst
- Data Analytics Consultant
- Metrics and Analytics Specialist
- Marketing Analyst
- Financial Analysis
- Operation Analyst
BONUS: Good Pay And More Job Opportunities
High demand and shortage of skilled workers – a perfect scenario to grab big opportunities. That’s exactly the situation in data analytics today. By just learning data analytics you can grab a good opportunity with a good paycheck.
In data analytics there isn’t a shortage of money but skilled people and this is your chance. You can go through this data analytics job listings on LinkedIn and see what paycheck companies are offering to get the right skilled people onboard.
That’s all about why you should learn data analytics now. If you’re convinced and looking forward to learning data analytics then SAS is the best choice. Check out A-Z SAS tutorials tailored for the beginners and advanced users.