Data science is a technological world nowadays that uses a very popular term. It is a multidisciplinary entity that deals with data in a structured and unstructured way. Uses scientific methods and mathematics to process data and extract knowledge from it. It works on the same concept of big data and data mining. It requires powerful hardware along with efficient algorithm and software programming to solve data problems or to manipulate data to get valuable knowledge from it.
Current information trends provide us with 80% of the data in an unstructured way while the remaining 20% is organized in a form for quick analysis. Unstructured or semi-structured details require processing in order to make them beneficial to the environment of entrepreneurs nowadays. Generally, this information or details are generated from a variety of sources such as text files, financial records, instruments, sensors, and forms of multimedia. Drawing meaningful and valuable insights from this information requires advanced algorithms and tools. This science proposes a valuable proposition for this purpose and this makes it a valuable science for the current world of technology.
How does data science derive insights from data?
1. For example, today’s internet sites maintain the huge volume of details or information regarding their customer base. Now, the online store wants to suggest product recommendations to each customer based on their past activity. The store got the complete information of the customers like previous purchase history, products browsing history, income, age and more. Here, science can be very useful by creating model trains using existing details and the shop can be able to 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.
2. Let’s take a look at another technological breakthrough where this science can be of great help. The best example here is the self-driving car. Details or live information from sensors, radars, lasers, and cameras generally create an ocean map for self-driving cars. The car uses this information to decide where to be fast, where to be slow, and when to overtake other vehicles. Data science uses an advanced machine learning algorithm for this. This is another best example to convey more about science and how it helps in decision making using available details or information.
3. Weather forecasting is another area in which this science plays a vital role. And here this science is used for predictive analysis. Details, information, facts, or figures collected from radars, ships, satellites, and aircraft used to analyze and build weather forecast models. Developed models that use science help predict the weather and accurately predict the occurrence of natural disasters as well. Without the flag, the data collected will be completely in vain.
Data Science Lifecycle
Capture: Science begins with data acquisition, input, extraction, and signal reception.
• Processing: This science effectively processes the acquired data using data mining, data aggregation and classification, data modeling and data summary.
• Maintenance: Science maintains processed data using data warehousing, data cleansing, data staging, and data engineering.
• Communication: This science communicates or serves data using data reports, data visualization, business intelligence and decision-making models.
• Analysis: This science analyzes data using exploratory or confirmatory process, predictive analysis, regression, text mining and qualitative analysis.
