In today’s digital age, data analysis has become an integral part of every industry, from marketing to finance and healthcare to education. The ability to extract meaningful insights from data has become crucial for businesses to make informed decisions, gain a competitive edge, and improve their bottom line. To keep up with this demand, many organizations are investing in data analysis training programs to equip their employees with the necessary skills to handle large datasets.
The Data Analysis Techniques training course covers a wide range of topics, including data collection and preparation, exploratory data analysis, statistical analysis, predictive modelling, and data visualization. It will benefit the participants how to analyse the data as, with so much data and so little time, knowing how to collect, curate, organise, and make sense of all of this potentially business-boosting information, as well as ensure business sustainability.
Have a look at some of the modules covered during the training course.
Data and Data Science
Data is everywhere. Every day, we generate vast amounts of data from various sources, including social media, sensors, and business transactions. To make sense of this data, we turn to data science and analytics, which involve using various techniques and tools to extract insights and knowledge from the data. In this module, we will explore the basics of data architecture and data analytics, as well as their importance in modern industries. We will also take a closer look at the KDD process and the CRISP-DM methodology for data mining.
Insights from Data Analytics
Data analytics is the process of examining data to uncover insights and gain a deeper understanding of patterns and trends. Insights from data analytics are critical in informing business decisions, improving processes, and developing strategies. In this module, we will explore some of the key concepts and tools used in data analytics, including descriptive statistics, data visualization, multivariate analytics, and different software applications.
Data Quality, Processing, and Forecasting
Data quality, processing, and forecasting play a significant role in data analytics. However, several issues can affect the accuracy of data analytics, including data quality issues, which we will explore in this module. Additionally, we will look at some of the methods used in data analytics, such as clustering analysis, regression, and predictive methods, and the overall importance of data analytics in modern business.
Data Mining and Representation
Data mining and representation are essential components of data analytics, which involves using various techniques to extract insights and knowledge from data. One of the critical aspects of data mining and representation is data visualization, which is the process of representing data in a visual format that can be easily understood. In this module, we will explore the basics of data visualization, including single-dimension, two-dimension, and multi-dimension data visualization, as well as histograms and other charts. We will also discuss charting within Excel, SPSS, and SAS, and the concept of Pareto analysis.
Functions and Regression Analysis
Data analytics involves using various techniques and tools to extract insights and knowledge from data. One of the critical components of data analytics is regression analysis, which involves modelling the relationship between one or more independent variables and a dependent variable. In this module, we will explore the basics of regression analysis, including linear, exponential, and polynomial regression. We will also discuss the analysis of variance (ANOVA), the Fourier transform, the theory of probability, and the concept of confidence limits.
In conclusion, the Data Analysis Techniques training course offered by Newage Learning is an excellent opportunity for anyone interested in data analytics to learn and develop their skills. The course provides comprehensive information on a complete set of data analytics, analysis techniques, and software used to analyze the available data. From the basics of data architecture to more advanced topics like regression analysis and Fourier transform, the course covers all the necessary aspects of data analytics. By completing this course, participants can acquire the skills and knowledge needed to succeed in modern business environments that rely heavily on data-driven insights. With the increasing demand for data analytics professionals, the Data Analysis Techniques training course can be an excellent investment for anyone looking to advance their career in this field.