Data is the most important part of the architecture in Data Science which organizes all the data by making it to be the most efficient by storing, managing, and realizing large data sets(data records) at high speeds also being cost-effective.Thus inorder to understand this futher let dive into the conceptual understanding first.
Computer Science , solving tomorrow’s problem with yesterday's bugs! Computer Science deals with the study of algorithms that define logic, data structures, computation, and databases. It creates a website and makes analytical algorithms to find trends of providing both theoretical and practical tools for user-friendly systems.
It is obviously understood that data and databases are among the core thoughts within the realm of computer science, accommodate, organize, and analyze data in its diversified forms and structures. RDBMS/SQL, NoSQL, cloud, and time series databases scale and flex to bridge that gap.
Information analysis and visualization are interpreted into meaningful actions that result from the application of visualization software, machine learning algorithms, and data mining techniques. It is powered and made more powerful by next-generation big data technologies like Hadoop and Spark.
Connecting the Dots: How Databases Fuel Data Science Innovations!!
Lets us understand with an example : fictional online-retail - ‘ShopMart’
In this example of online retail 'ShopMart':
- The Role of computer science ensures creating secure, scalable, and user-friendly systems.
- Database structure, design, and normalization ensure a secure system while maintaining data storage and organizing on types of data. Transaction management guarantees reliable operations and integrity of data even in case of system failure.
- Sales data analysis depicts trends and facilitates better purchase experiences.It aids in the optimization of purchase experiences by identifying the trends and recommending relevant merchandise.
Descriptive statistics algorithms, collaborative filtering tools like Tensorflow, Seaborn, together with data mining and big data technologies: Hadoop and Spark used.
Thus Computer Science Driving insights and innovation through data.
Top comments (0)