Financial Data Analysis Best Practices
October 08- October 12 \ 2023 : Kuwait
October 08- October 12 \ 2023 : Amman
November 05- October 09\ 2023: Dubai
Introduction
Corporate ethos which demands continual improvement in work place efficiencies and reduced operating, maintenance, support service and administration costs means that managers, analysts and their advisors are faced with ever-challenging analytical problems and performance targets. To make decisions which result in improved business performance it is vital to base decision making on appropriate analysis and interpretation of numerical data.
Objectives
Participants attending the training seminar will:
Þ This IACT Data Analysis Techniques training course aims to provide those involved in analysing numerical data with the understanding and practical capabilities needed to convert data into information via appropriate analysis, and then to represent these results in ways that can be readily communicated to others in the organisation.
Þ Objectives include:
Þ To provide delegates with both an understanding and practical experience of a range of the more common analytical techniques and representation methods for numerical data
Þ To give delegates the ability to recognize which types of analysis are best suited to particular types of problems
Þ To give delegates sufficient background and theoretical knowledge to be able to judge when an applied technique will likely lead to incorrect conclusions
Þ To provide delegates with a working vocabulary of analytical terms to enable them to converse with people who are experts in the areas of data analysis, statistics and probability, and to be able to read and comprehend common textbooks and journal articles in this field
Þ To introduce some basic statistical methods and concepts
Þ To explore the use of Excel 2010 or 2013 for data analysis and the capabilities of the Data Analysis Tool Pack
Þ It should be noted that the course does not cover the subjects of data acquisition, databases, data management, data warehousing or the analysis of text-based information.
Who Should Attend?
Ü This IACT Data Analysis Techniques training course has been designed for professionals whose jobs involve in the manipulation, representation, interpretation and/or analysis of data. Familiarity with a PC and in particular with Microsoft Excel (2003, 2007, 2010 or 2013) is assumed.
Þ This IACT training course involves extensive computer-based data analysis using Excel 2010 and therefore delegates will be expected to be numerate and to enjoy working with numerical data on a computer.
Course Methodology
The course uses self-assessments and a wide mix of business cases that promote healthy discussions around the importance of managing multiple tasks, deadlines and priorities. Participants will benefit from role plays covering workplace challenges related to handling tasks, deadlines and priorities. They will learn how to deal with conflicts that may arise as a result. Interactive team exercises are also used with each team presenting their findings and comments.
This interactive training course includes the following training methodologies as a percentage of the total tuition hours:
- 30% Lectures, Concepts, Role Play
- 30% Workshops & Work Presentations, Techniques
- 20% Based on Case Studies & Practical Exercises
- 20% Videos, Software & General Discussions
Pre and Post Test
Outline
DAY 1:
The Basics
Þ Sources of data, data sampling, data accuracy, data completeness, simple representations, dealing with practical issues
Fundamental Statistics
Þ Mean, average, median, mode, rank, variance, covariance, standard deviation, “lies, more lies and statistics”, compensations for small sample sizes, descriptive statistics, insensitive measures
DAY 2 :
Basics of Data Mining and Representation
Þ Single, two and multi-dimensional data visualisation, trend analysis, how to decide what it is that you want to see, box and whisker charts, common pitfalls and problems
Data Comparison
Þ Correlation analysis, the auto-correlation function, practical considerations of data set dimensionality, multivariate and non-linear correlation
DAY 3 :
Histograms and Frequency of Occurrence
Þ Histograms, Pareto analysis (sorted histogram), cumulative percentage analysis, the law of diminishing return, percentile analysis
Frequency Analysis
Þ The Fourier transform, periodic and a-periodic data, inverse transformation, practical implications of sample rate, dynamic range and amplitude resolution
DAY 4 :
Regression Analysis and Curve Fitting
Þ Linear and non-linear regression, order; best fit; minimum variance, maximum likelihood, least squares fits, curve fitting theory, linear, exponential and polynomial curve fits, predictive methods
Probability and Confidence
Þ Probability theory, properties of distributions, expected values, setting confidence limits, risk and uncertainty, ANOVA (Analysis of Variance)
DAY 5 :
Some More Advanced Ideas
Þ Pivot tables, the Data Analysis Tool Pack, internet-based analysis tools, macros, dynamic spreadsheets, sensitivity analysis
Schedule:
08:30 – 10:15 First Session
10:15 – 10:30 Coffee Break
10:30 – 12:15 Second Session
12:15 – 12:30 Coffee Break
12:30 – 14:00 Third Session
Fees:
The Fee for the seminar, including instruction materials, documentation, lunch, coffee/tea breaks & snack is: 3.750USD$