What Is Data Science?

Data science is a current technological world using a very common term. It is a multidisciplinary entity that processes data in a structured and unstructured way. It uses scientific and mathematical methods to process data and extract knowledge from it. It works on the same concept as Big Data and Data Mining. It requires powerful hardware along with efficient algorithm and software programming to solve the data problems or process the data to gain valuable insight from it.

Current information trends give us 80% of the data in an unstructured way, while the rest 20% is structured in a format for quick analysis. Unstructured or semi-structured details require processing to be useful for today’s business environment. In general, this information or details are generated from a wide variety of sources, such as text files, financial records, instruments and sensors, and multimedia forms. Extracting meaningful and valuable insights from this information requires advanced algorithms and tools. This Science is proposing a value proposition for this purpose and this is making it a valuable science for today’s technological world.

How does data science extract insights from data?

  1. For example, today’s online sites hold a large volume of 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 obtained all the information of the customers, such as the history of previous purchases, the products they are looking for in the history, the income, the age and some more. Here, science can be of great help by generating model trains using existing details and the store could recommend accurate products to the customer base at regular intervals. Processing information for this purpose is a complex activity, but science can do wonders for this purpose.
  2. Let’s see another technological advance in which this science can be of great help. The autonomous car is the best example here. Live details or information from sensors, radars, lasers, and cameras typically create the map of the environment 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 an advanced machine learning algorithm for this purpose. This is another better instance to convey more about the science and how it helps in decision making using the details or information available.
  3. Weather forecasting is another area where this science plays a vital role. Here, this science is used for predictive analytics. 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 the weather and also accurately predict the occurrence of natural calamities. Without science, the data collected will be totally in vain.

Data Science Lifecycle

• Capture: The science begins with data acquisition, data entry, data extraction, and signal reception.

• Processing: This science processes acquired data efficiently through data mining, data clustering and classification, data modeling, and data summarization.

• Maintenance: The Science maintains the processed data through data storage, data cleansing, data organization, and data architecture.

• Communicate: This science communicates or serves data using data reporting, data visualization, business intelligence, and decision-making models.

• Analytics: This science analyzes data using exploratory or confirmatory processes, predictive analytics, regression, text mining, and qualitative analysis.

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