1 / 9

BASIC RULES OF RUNNING DATA SCIENCE

Data science is the learning of data it involves developing methods of reporting storing and analyzing data to effectively extract useful top make an informed decision the goal of data science is to gain insight and knowledge from any type of data for both structured and unstructured.

WebBrains
Download Presentation

BASIC RULES OF RUNNING DATA SCIENCE

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. DATA SCIENCE By Webbrains

  2. What is Data Science? Data science continues to evolve as one of the most promising and in-demand career paths for skilled professionals. Today, successful data professionals understand that they must advance past the traditional skills of analyzing large amounts of data, data mining, and programming skills. In order to uncover useful intelligence for their organizations, data scientists must master the full spectrum of the data science life cycle and possess a level of flexibility and understanding to maximize returns at each phase of the process.

  3. The Data Science Lifecycle

  4. The Data Science Life Cycle Capture: Data Acquisition, Data Entry, Signal Reception, Data Extraction. This stage involves gathering raw structured and unstructured data. Maintain: Data Warehousing, Data Cleansing, Data Staging, Data Processing, Data Architecture. This stage covers taking the raw data and putting it in a form that can be used. Process: Data Mining, Clustering/Classification, Data Modeling, Data Summarization. Data scientists take the prepared data and examine its patterns, ranges, and biases to determine how useful it will be in predictive analysis. Analyze: Exploratory/Confirmatory, Predictive Analysis, Regression, Text Mining, Qualitative Analysis. Here is the real meat of the lifecycle. This stage involves performing the various analyses on the data. Communicate: Data Reporting, Data Visualization, Business Intelligence, Decision Making. In this final step, analysts prepare the analyses in easily readable forms such as charts, graphs, and reports

  5. How Does Data Science Work? Data science involves a plethora of disciplines and expertise areas to produce a holistic, thorough and refined look into raw data. Data scientists must be skilled in everything from data engineering, math, statistics, advanced computing and visualizations to be able to effectively sift through muddled masses of information and communicate only the most vital bits that will help drive innovation and efficiency.

  6. Why Become a Data Scientist? Glassdoor ranked data scientist among the top three jobs in America since 2016.4 As increasing amounts of data become more accessible, large tech companies are no longer the only ones in need of data scientists. The growing demand for data science professionals across industries, big and small, is being challenged by a shortage of qualified candidates available to fill the open positions. The need for data scientists shows no sign of slowing down in the coming years. LinkedIn listed data scientist as one of the most promising jobs in 2021, along with multiple data-science-related skills as the most in- demand by companies.

  7. CAREER IN DATA SCIENCE Data science professionals are rewarded for their highly technical skill set with competitive salaries and great job opportunities at big and small companies in most industries. With almost 6,000 open positions listed on Glassdoor, data science professionals with the appropriate experience and education have the opportunity to make their mark in some of the most forward-thinking companies in the world. Below are the average base salaries for the following positions: Data analyst: $69,517 Data scientist: $117,212 Senior data scientist: $142,258 Data engineer: $112,493 Gaining specialized skills within the data science field can distinguish data scientists even further. For example, machine learning experts utilize high-level programming skills to create algorithms that continuously gather data and automatically adjust their function to be more effective.

  8. SKILLS REQUIRED BECOME A DATA SCIENTIST There are certain programming languages needed to analyze the data and to exhibit in an exemplary way. One needs to gain a good knowledge of python to become a good data scientist. For data management purpose you need to have knowledge about MySQL. You should have good knowledge of data visualization and beside this, it would be great if you have a grip on reporting and writing skills.

  9. THANK YOU!! To Get More Information About Data Science Join Us At Webbrains . E-73, South Extension Part-1 New Delhi - 110049 India info@webbrains.com +918892636363

More Related