Sherlock Holmes would have loved living in the twenty-first century. We are drenched in data, and so many of our problems (including a murder mystery) can be solved using large amounts of data existing at personal and societal levels. These days it is fair to assume that most people are familiar with the term "data." We see it everywhere. And if you have a cellphone. then chances an: this is something you have encountered frequently. Assuming you are a "connected" person who has a smartphone, you probably have a data plan from your phone service provider. The most common cellphone plans in the USA include unlimited talk and text, and a limited amount of data - 5 GB, 20 GB. etc. And if you have one of these plans, you know well that you are -using data" through your phone and you get charged per usage of that data. You understand that chocking your email and posting a picture on a social media platform consumes data And if you are curious (or the(ty) sort, you calculate how much data you consume monthly and pick a plan that fits your needs. You may also have come across terms like "data sharing," when picking a family plan for your phone(s). But there are other places where you may have encountered the notion of data sharing. For instance, if you have privacy concerns, you may want to know if your cellphone company -shares" data about you with others (including the government).
And finally, you may have heard about "data warehouses." as if data is being kept in big boxes on tall shelves in middle•of-nowhere locations.
WHAT IS THE IMPORTANCE OF DATA SCIENCE?
According to IDC, worldwide data will reach 175 zettabytes by 2025. Companies may use data science to quickly evaluate massive amounts of data from numerous sources and gain important insights to make better data-driven decisions. Marketing, healthcare, finance, banking, policy work, and other industries all employ data science to some extent. That clarifies the significance of Data Science.
THE VALUE OF DATA SCIENCE IN THE WORKPLACE
Data Science is significant in business for a variety of reasons. Enterprises can use data science to monitor, track, and record performance measures to improve decision-making across the board. Companies can use trend analysis to make crucial decisions about how to better engage customers, improve corporate performance, and increase profitability. Data Science models can replicate a variety of operations using existing data. As a result, businesses can create a strategy for achieving the greatest possible results. By merging existing data with other data points and producing meaningful insights, Data Science assists firms in identifying and refining target audiences. Recruiters can also benefit from data science by integrating data pieces to find applicants that best meet their company's needs.
A data science platform's advantages
By allowing teams to exchange code, findings, and reports, a data science platform lowers repetition and promotes innovation. By simplifying management and adopting best practices, it eliminates bottlenecks in the flow of work.
In general, the best data science platforms aim to:
Make data scientists more productive by assisting them in accelerating and delivering models in a more timely and error-free manner.
Make it easier for data scientists to work with big amounts of data and different types of data.
Deliver bias-free, auditable, and reproducible artificial intelligence to the company.
Expert data scientists, citizen data scientists, data engineers, and machine learning engineers or specialists are among the users who benefit from data science platforms. A data science platform, for example, might allow data scientists to publish models as APIs, making it simple to incorporate them into other applications. Without having to wait for IT, data scientists may access tools, data, and infrastructure.
In the market, demand for data science platforms has skyrocketed. In fact, over the next five years, the platform industry is estimated to increase at a compound annual rate of more than 39%, reaching US$385 billion by 2025.
What is the best way to get started learning data science?
You can't learn what you need to know about data science in a year or two of study and call yourself a data scientist. Instead, begin studying right away, whether on your own or through official instruction and then put what you've learned into practice in a real-world situation. Rep until you've either fixed all of the world's issues or you've retired.
Fortunately, open-source software, which is freely available to anybody, is at the heart of data science. Try a Linux distribution as a first start, as it might serve as a good platform for your work. Linux is an open-source operating system, which means it's not only free to use but also extremely adaptable, making it ideal for a field that requires ongoing adaptation. Python, a popular data science language, is also included with Linux. The NumPy and Pandas libraries were created with number crunching and data analytics in mind, and their documentation is extensive.
One of the most difficult aspects of learning a new language or library, as is often the case, is figuring out how to put the tools to use in your daily life. In contrast to many other subjects, data science has no wrong answers. Any set of data can be used to apply data science ideas. At worst, you'll learn that two sets of data have no association, or that an apparently random event has no pattern. However, because this is real research, you will not only have learnt about data science, but you will have actually validated or disproven a hypothesis.
Open data sets are easier to find thanks to open source's influence. Data sets are accessible from Data.gov, the World Bank, Google (including NASA, GitHub, the US Census, and other sources), and many others. These are fantastic resources for learning how to scrape the web for data, parse it into an easily processable format, and analyze it using specialist libraries.
Conclusion
With a presence in almost every industry, Data Science employment demand is expected to skyrocket in the future. Data Science is becoming increasingly important with each passing day. Jigsaw Academy provides a variety of high-quality Data Science courses to help tomorrow's Data Scientists get started. If learners are seeking a thorough Full Stack Data Science curriculum, they can enrol in the Full Stack Data Science Program (FSDS). This industry-recommended and validated 6-month online program is connected to the SSC NASSCOM curriculum.