Analytics is the science of extracting insights and patterns from data sets. It typically involves collecting, cleaning, organizing, analyzing, and visualizing data in order to gain insight for making better business decisions. With analytics, data scientists and analysts create models to understand complex problems and develop data- driven solutions. They also use statistics and predictive analytics to identify trends and build custom predictive models with algorithms to make better decisions. Skills that can be gained from studying analytics include :
1. Data Analysis and Visualization :
data analysis and visualization is essential for understanding the data and extracting insights from it. Skills include statistical modeling, linear regression, machine learning, etc. 2. Machine Learning :
the ability to use and create data models to understand and make predictions from data. Skills include supervised and unsupervised learning approaches, neural networks, deep learning, and natural language processing. 3. Programming and Software Development :
data analytics often require the use of specific programming languages and tools. Skills include Python, R, SQL, MATLAB, and Big Data technologies like Hadoop, Spark, and Hive. 4. Data Transformation :
understanding data and manipulating it so it can be used for analysis. Skills include data wrangling, data mining, and ETL (Extract, Transform, Load). 5. Data Science :
a skill set that combines the different disciplines of data analytics to solve real- world problems and build data- driven products. Skills include predictive modeling, demand forecasting, and clustering.
