Bingo!! We have found the perfect match for you. From finding a date on tinder to finding a pair of matching shoes to your Halloween costume just under 90 seconds. How does my computer know everything about me?
Ever wondered when you open your Netflix account it always knows what you would want to watch and have a separate section for you which says “Netflix top picks for you”. No, don’t worry your neighbor next door did not spy on you and sent your information to Netflix. That is where data science comes into the picture. In simpler terms, it is the hidden patterns extracted from the raw data to explore, predict and infer precise information from your customer. In earlier times, there was a fixed set of a source through which all these big giants used to receive data in order to process and use it. As the web grew from dozens to million pages, automation to store and process the huge amount of data quickly was required. Now when Hadoop and other frameworks have successfully solved the problem of storage, the focus is transferred to the processing of data in order to provide detailed insights from large and complex data. The data which is generated from a number of channels such as surveys, internet searches, financial logs, purchases, sensors, instruments, and multimedia forms require advanced analytical tools and algorithms to draw meaningful insights out of it. “Marketing without data is like driving with your eyes closed.”-Dan Zarella. Data science enables the organization to make evidence-based decisions to increase profitability and operational efficiency.
Data science and Data Analysts have been the Buzzword, you want to know why? Did you know how much a data analyst is paid? According to one of the reports published by PWC, US average advertised annual salary for a data analyst is $77,500-$118,750. And it is predicted that by 2020, there will be more than 2.7 million big data and analytics jobs open to qualified professionals. Just imagine a data analyst sitting In United States of America predict what a customer sitting in Australia is going to purchase next on Amazon and accordingly, the company can recommend the product with a customized offer designed especially for him/her in order to convert a prospective customer into a full-time customer or create one-to-one marketing campaigns.
So metaphorically it is like given a box of LEGO, you have different kinds of blocks (Structured data and unstructured data) and now it depends on you how you use your creativity and knowledge (Python, R, Spark) to make a beautiful Lego model which is definitely going to sell.
“Torture the data and it will confess to anything.” –Ronaldo Coase. Data can be in any form like text, on paper, or bytes stored in electronic memory. It is very difficult to process such a vast complex unstructured data. Therefore, machine learning is incorporated in data learning which automates the data processing. It not only speeds up the process but also identifies the occurrence of a particular event in the future. After collecting and processing the information derived from this data, analysts interpret, convert and summarize the data for decision-makers to give companies an edge in the fierce industry. More and more data provides companies to make an informed business decision and that is why the future belongs to the data scientists.