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Related Concept Videos

Performing a Simple Data Analysis using MS-Excel Function01:17

Performing a Simple Data Analysis using MS-Excel Function

Microsoft Excel offers a suite of functions and tools ideal for statistical analysis, making it accessible to students and researchers. This article outlines fundamental Excel functions pivotal for data analysis.
SUM: This function calculates the total sum of a range of values. It's the foundation for aggregating data, essential for determining overall trends and totals in datasets.
AVERAGE: It computes the mean value of a given set of numbers, providing a quick insight into the central...
Statistical Analysis System (SAS)01:14

Statistical Analysis System (SAS)

SAS, short for Statistical Analysis System, is a powerful data analysis, management, and visualization tool. Developed by the SAS Institute in the early 1970s, SAS has evolved into a comprehensive software suite used across various industries for statistical analysis, business intelligence, and predictive modeling.
Applications: SAS finds applications in numerous fields, including healthcare for clinical trial analysis, finance for risk assessment, marketing for customer data analysis, and...
Statgraphics01:10

Statgraphics

Statgraphics is a comprehensive statistical software suite designed for both basic and advanced data analysis. Originating in 1980 at Princeton University under Dr. Neil W. Polhemus, it was one of the pioneering tools for statistical computing on personal computers, with its public release in 1982 marking an early milestone in data science software. Over the years, it has evolved into a robust platform for data science, offering tools for regression analysis, ANOVA, multivariate statistics,...
Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
Manipulation and Analysis01:21

Manipulation and Analysis

GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...
Overview of Microsoft Excel as a Data Analysis Tool01:13

Overview of Microsoft Excel as a Data Analysis Tool

Microsoft Excel is a cornerstone tool for data analysis and statistical operations, offering a wide array of functionalities to manage, analyze, and visualize data efficiently. Recognized for its versatility, Excel facilitates the performance of basic to complex statistical operations, serving as an indispensable asset for analysts, researchers, and students alike. Excel's significance in data analysis emanates from its spreadsheet environment, where data can be organized in rows and columns,...

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Updated: May 17, 2026

Facilitating the Analysis of Immunological Data with Visual Analytic Techniques
10:58

Facilitating the Analysis of Immunological Data with Visual Analytic Techniques

Published on: January 2, 2011

Making advanced analytics work for you.

Dominic Barton1, David Court

  • 1McKinsey.

Harvard Business Review
|October 19, 2012
PubMed
Summary

Senior leaders should embrace big data analytics to improve daily operations. Implementing advanced analytics requires identifying relevant data, building focused models, and fostering a data-driven culture from the top down.

Area of Science:

  • Business Analytics
  • Data Science
  • Organizational Behavior

Background:

  • Many senior leaders underestimate the practical value of big data.
  • Translating advanced analytics into daily operations presents challenges.
  • A strategic approach is needed to leverage big data effectively.

Purpose of the Study:

  • To provide a guide for leaders and managers on implementing big data strategies.
  • To demonstrate how to translate advanced analytics into tangible business practices.
  • To highlight the importance of cultural transformation in big data adoption.

Main Methods:

  • Analysis of case studies from dozens of companies.
  • Development of a three-step framework for big data implementation.

Related Experiment Videos

Last Updated: May 17, 2026

Facilitating the Analysis of Immunological Data with Visual Analytic Techniques
10:58

Facilitating the Analysis of Immunological Data with Visual Analytic Techniques

Published on: January 2, 2011

  • Focus on identifying relevant data, building performance-focused analytics models, and enabling cultural integration.
  • Main Results:

    • Companies must strategically acquire and manage data.
    • Analytics models should be tailored to specific business goals for optimal performance.
    • Successful implementation hinges on transforming organizational capabilities and culture.

    Conclusions:

    • Embracing big data is crucial for business success and requires more than just data processing.
    • A cultural shift towards data-driven decision-making is essential for realizing the full benefits of big data.
    • Effective big data utilization leads to significant, often underestimated, business payoffs.