Data science is a modern technological world that uses a very common term. It is a multidisciplinary entity that handles data in a structured and unstructured way. Use 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 data problems or process data to gain valuable insight into them.
Current information trends provide us with 80% of the data in an unstructured way, while the remaining 20% is structured in 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 is generated from a wide variety of sources, such as text files, financial records, instruments and sensors, and multimedia forms. To obtain meaningful and valuable information from this information, algorithms and advanced tools are required. 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 information from data?
1. For example, today’s online sites maintain a high volume of details or information related to their customer base. Now, the online store wants to propose product recommendations for each customer based on their previous activity. The store got all the customer information like past purchase history, history browsing products, income, age and some more. Here, science can go a long way in proposing train models 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 driverless car is the best instance here. Live details or information from sensors, radars, lasers, and cameras generally create the surrounding map for driverless 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 best instance to convey more about science 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 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. Models developed using science help forecast the weather and also accurately predict the occurrences of natural calamities. Without science, the data collected will be totally in vain.
Data science life cycle
• Capture: Science begins with data acquisition, data entry, data extraction, and signal reception.
• Processing: This science processes acquired data effectively using data mining, data grouping and classification, data modeling, and data summarization.
• Maintenance: The Science maintains the processed data through data storage, data cleaning, data staging and data architecture.
• Communication: This science communicates or serves data using data reporting, data visualization, business intelligence, and decision-making models.
• Analysis: This science analyzes data using an exploratory or confirmatory process, predictive analysis, regression, text mining, and qualitative analysis.