What is data science?

Data Science is a modern technology world using a very common term. It is a multidisciplinary entity that handles data in a structured and unstructured manner. It uses scientific methods and mathematics 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 extract valuable insights from it.

Current information trends provide us with 80% of the data in unstructured form, while the remaining 20% ​​is provided in a structured format for quick analysis. The unstructured or semi-structured details need to be processed to make them usable for today’s entrepreneurial environment. Generally, this information or details are generated from a variety of sources such as text files, financial logs, instruments and sensors, and multimedia forms. Extracting meaningful and valuable insights from this information requires advanced algorithms and tools. This science proposes a value proposition to that end, making it a valuable science for today’s technological world.

How does data science derive insights from data?

1. For example, today’s online sites maintain the vast amount of details or information related to their customer base. Now the online shop would like to propose product recommendations to each customer based on their past activities. The store got the entire information of the customers like past purchase history, products browsing history, income, age and some more. This is where science can be of great help, creating train models using the details that are available and being able to periodically recommend accurate products to the customer base. Processing information for this purpose is a complex activity, but science can work wonders for this purpose.

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2. Let’s explore another technological breakthrough where this science can be of great help. The self-driving car is the best example here. Live details or information from sensors, radars, lasers and cameras usually form the environment map 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 algorithms for this purpose. This is another best example to teach more about science how it helps in decision making using available details or information.

3. Weather forecasting is another area where this science plays an important role. Here, this science is used for predictive analysis. Details or information or facts or figures collected from radars, ships, satellites and airplanes and used to analyze and create models for weather forecasting. The models developed with the help of science help to predict the weather and also accurately predict the occurrence of natural disasters. Without science, the collected data is completely in vain.

Data science lifecycle

• Acquisition: Science begins with data acquisition, data entry, data extraction, and signal reception.

• Processing: This science effectively processes the collected data using data mining, data clustering and classification, data modeling and data summarization.

• Maintenance: The Science manages the processed data using data warehousing, data cleansing, data delivery and data architecture.

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

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