Makenow | 10 FEB 2022

HOW Data science is affective in our day activities?
To better understand of data science lets see how its affective in our day to day activities.Its an Monday morning and I have to get to office before my meeting starts.So I quickly open up uber and look for cabs,but there’s something unsual the gab reads a comparatively higher at this hour of the day.why does this happen?well,obviously because Monday mornings are P cars and evryone is rushing off to work.The high demand for cabs leads to increase in the cab fares.we all know this but how is all of this implemented.Data science is at the heart of ubers pricing algorithm.The surge pricing algorithm ensures that their passengers always get a ride when they need one.even it comes at the cost of inflated prices.

Uber implements data science to find out which neighborhoods will be the busiest so that it can activate search pricing to get more drivers on the this manner over maximized the number of rides it can provide and hence benefit from this.Uber surge pricing algorithm uses datascience.
Why do you want to learn data science?
5 valuable reasons to pursue data science as a career
In 2019, Salesforce acquired Tableau and Google acquired Looker, a startup in the data analytics space. These two stories showed how businesses across the globe are shifting their focus to data-driven goals. Some more stories highlighting worth here are
Lionbridge acquired Gengo
DataRobot acquired three companies – ParallelM, Cursor, and Paxata
HPE acquired MapR
Thinking about getting started with a career in Data Science? There cannot be a better time than now!
Did you know that Glassdoor discovered that a data scientist’s role is one of the top-scoring jobs in 2020? It did not just rank in terms of its demand but also on job satisfaction metrics. Learning data science today is not tough anymore. You could take up professional courses or even resort to an array of online courses to kick start your journey as a data scientist. If you are an undergraduate with basic knowledge of programming and great analytical skills, you can move along the data science curve.
In business, the use of Data Science is in varied domains. This gives you ample scope to learn and grow in the role of a data scientist. Here are the 5 reasons why you must learn data science.
1. Great career trajectory with data science – Yes, you will have rewarding career growth in this field. Data scientists bring tons of value to organizations and are the most sought after roles in today’s scenario and will be in the future.
2. Great potential to branch out with different options – You can choose to branch out as a data engineer, an analyst, or an ML engineer, or even a data science manager.
3. Highest salary takeaway quotient – As a Data scientist, you can expect to take away a great salary package. Usual data scientists are paid great salaries, sometimes much above the normal market standards due to the critical roles and responsibilities.
4. Become a decision-maker – Not every job opportunity will give you the power to make informed business decisions. For a data scientist, that is the core responsibility. That is how you kick start. The credibility will always be rewarded because of the lack of talent pool in the ecosystem.
5. Less competitive because it is a highly analytical role – Competition is less, but demand is not. With a limited talent pool, there is always a challenge for businesses to hire in these roles. Once you join in, you become a decision-maker and face less competition from your organization’s peers for you having a unique skill set.
What is the need for Data Science?
The reason why we need data science is the ability to process and interpret data. This enables companies to make informed decisions around growth, optimization, and performance. Demand for skilled data scientists is on the rise now and in the next decade. For example, machine learning is now being used to make sense of every kind of data – big or small. Data metrics are driving every business decision. The job market scenario for data scientists will grow to almost 11.5M by 2026 [U.S Bureau of Labor Statistics]. Companies are busy ramping up their data science workforce to enable higher efficiency and planning.
What is Data Science useful for?
Data science is a process that empowers better business decision-making through interpreting, modeling, and deployment. This helps in visualizing data that is understandable for business stakeholders to build future roadmaps and trajectories. Implementing Data Science for businesses is now a mandate for any business looking to grow.