Capture What Data Science is and Lifecycle of a Data Scientist

By ridhigrg |Email | Aug 16, 2019 | 1383 Views

Data science is a present-day technology world using a very common term. It is a multi-disciplinary entity that deals with data in a structured and unstructured manner. It uses scientific methods and mathematics to process data and to extract knowledge from it. It works on the same concept as Big Data and Data Mining. It requires powerful hardware along with an efficient algorithm and software programming to solve the data problems or to process the data for obtaining valuable knowledge from it.

The present information trends are providing us 80% of data in unstructured mannered while rest 20% structured in format for quick analyzing. The unstructured or semi-structured details require processing in order to make it useful for the present-day entrepreneur environment. Generally, this information or details are generated from the wide varieties of sources such as text files, financial logs, instruments and sensors, and multimedia forms. Drawing meaningful and valuable insights from this information require advanced algorithms and tools. This Science is proposing a value proposition for this purpose and this is making it a valuable science for the present-day technological world.

How Data Science Drawing Insights from Data?
1. For example, present-day online sites are maintaining the huge volume of the details or information pertaining to their customer base. Now, the online store wants to propose product recommendations for each customer based on their past activity. The store got the entire information of the customers like past purchase history, products browsing the history, income, age and some more. Here, the science can be a great help by coming up with train models using the existing details and store could be able to recommend precise products to the customer base at the regular intervals. Processing information for this purpose is a complex activity, but the science can do wonders for this purpose.

2. Let us look into another technological breakthrough where this science can be a great help. The self-driving car is the best instance here. Live details or information from sensors, radars, lasers, and cameras generally create the map of surroundings for self-driving cars. The car uses this information to decide where to be fast and where to be slow and when to overtake other vehicles. Data science uses advanced machine learning algorithm for this purpose. This is another best instance to convey more about the science how it helps in decision-making using available details or information.

3. Weather forecasting is another area where this science plays a vital role. Here, this science used for predictive analysis. Details or information or facts or figures collected from radars, ships, satellites, and aircraft used to analyze and build models for weather forecasting. The developed models using science help forecast weather and to predict accurately the occurrences of the natural calamities too. Without science, the data collected will be totally in vain.

Life Cycle of Data Science
  • Capturing: The Science starts with data acquisition, data entry, data extraction, and signal reception.
  • Processing: This science process acquired data effectively using data mining, data clustering & classification, data modeling, and data summary.
  • Maintaining: The Science maintains the processed data using data warehousing, data cleansing, data staging, and data architecture.
  • Communicating: This science communicates or serves data using data reporting, data visualization, business intelligence, and decision-making models.
  • Analyzing: This Science analyzes data using exploratory or confirmatory process, predictive analysis, regression, text mining, and qualitative analysis.

Source: HOB