000			01682nam a2200205 4500
005			20260311164618.0
008			260311b |||||||| |||| 00| 0 eng d
020			_a9788198543394
082			_a658.4038 MAL
100			_aMalik, Sangeeta
245			_aBusiness Analytics: _bempowering decisions with data
260			_aNew Delhi: _bAne; _cc2026.
300			_a249p.
500			_aIt contains glossary.
520			_aThe Business Analytics course offers a comprehensive understanding of key concepts, tools, and techniques essential for data-driven decision-making. It begins with the evolution of business analytics, the analytics process, and an overview of roles like data scientists, data engineers, and business analysts, along with an introduction to R programming. The course delves into data warehousing and mining, covering ETL processes, star schemas, and data mining applications in industries such as retail, healthcare, insurance, and telecommunications. Data visualization is another key focus, teaching students various visualization techniques, cross-tabulation, chart creation, and tools like Tableau, as well as data modelling concepts. The course also explores the three primary types of analytics: descriptive (mean, median, mode, standard deviation), predictive (linear and multivariate regression), and prescriptive (graph analysis, simulation, optimization). By blending theory and practical applications, this course equips students with the skills needed to pursue careers and make data-driven decisions in business.
650			_aBusiness Management
700			_aPriyadarshnie, Sundram _eAuthor
700			_aGarg, Neha _eAuthor
942			_2ddc _n0 _cC
999			_c30698 _d30698