/  Data Analysis Techniques Training

Data Analysis Techniques Training

BMC Training provides a training course in Data Analysis Techniques in Maintenance Engineering Training

Course Title
Venue
Start Date
End Date
  • Istanbul
    27 - 1 - 2019
    31 - 1 - 2019
  • Bali
    27 - 1 - 2019
    31 - 1 - 2019
  • Singapore
    27 - 1 - 2019
    31 - 1 - 2019
  • Washington
    27 - 1 - 2019
    31 - 1 - 2019
  • Kuala Lumpur
    20 - 1 - 2019
    24 - 1 - 2019
  • Rome
    20 - 1 - 2019
    24 - 1 - 2019
  • Barcelona
    20 - 1 - 2019
    24 - 1 - 2019
  • Zurich
    20 - 1 - 2019
    24 - 1 - 2019
  • Dubai
    13 - 1 - 2019
    17 - 1 - 2019
  • Paris
    13 - 1 - 2019
    17 - 1 - 2019
  • Hong Kong
    13 - 1 - 2019
    17 - 1 - 2019
  • London
    6 - 1 - 2019
    10 - 1 - 2019
  • Madrid
    6 - 1 - 2019
    10 - 1 - 2019
  • Munich
    6 - 1 - 2019
    10 - 1 - 2019
  • Berlin
    6 - 1 - 2019
    10 - 1 - 2019
  • New York
    6 - 1 - 2019
    10 - 1 - 2019
  • Dubai
    24 - 2 - 2019
    28 - 2 - 2019
  • Paris
    24 - 2 - 2019
    28 - 2 - 2019
  • Hong Kong
    24 - 2 - 2019
    28 - 2 - 2019
  • Kuala Lumpur
    17 - 2 - 2019
    21 - 2 - 2019
  • Rome
    17 - 2 - 2019
    21 - 2 - 2019
  • Barcelona
    17 - 2 - 2019
    21 - 2 - 2019
  • Zurich
    17 - 2 - 2019
    21 - 2 - 2019
  • Istanbul
    10 - 2 - 2019
    14 - 2 - 2019
  • Bali
    10 - 2 - 2019
    14 - 2 - 2019
  • Singapore
    10 - 2 - 2019
    14 - 2 - 2019
  • Washington
    10 - 2 - 2019
    14 - 2 - 2019
  • London
    3 - 2 - 2019
    7 - 2 - 2019
  • Madrid
    3 - 2 - 2019
    7 - 2 - 2019
  • Munich
    3 - 2 - 2019
    7 - 2 - 2019
  • Berlin
    3 - 2 - 2019
    7 - 2 - 2019
  • New York
    3 - 2 - 2019
    7 - 2 - 2019
  • Istanbul
    17 - 3 - 2019
    21 - 3 - 2019
  • Bali
    17 - 3 - 2019
    21 - 3 - 2019
  • Singapore
    17 - 3 - 2019
    21 - 3 - 2019
  • Washington
    17 - 3 - 2019
    21 - 3 - 2019
  • Kuala Lumpur
    10 - 3 - 2019
    14 - 3 - 2019
  • Rome
    10 - 3 - 2019
    14 - 3 - 2019
  • Barcelona
    10 - 3 - 2019
    14 - 3 - 2019
  • Zurich
    10 - 3 - 2019
    14 - 3 - 2019
  • Dubai
    3 - 3 - 2019
    7 - 3 - 2019
  • Paris
    3 - 3 - 2019
    7 - 3 - 2019
  • Hong Kong
    3 - 3 - 2019
    7 - 3 - 2019
  • London
    24 - 3 - 2019
    28 - 3 - 2019
  • Madrid
    24 - 3 - 2019
    28 - 3 - 2019
  • Munich
    24 - 3 - 2019
    28 - 3 - 2019
  • Berlin
    24 - 3 - 2019
    28 - 3 - 2019
  • New York
    24 - 3 - 2019
    28 - 3 - 2019
  • Dubai
    28 - 4 - 2019
    2 - 5 - 2019
  • Paris
    28 - 4 - 2019
    2 - 5 - 2019
  • Hong Kong
    28 - 4 - 2019
    2 - 5 - 2019
  • Kuala Lumpur
    7 - 4 - 2019
    11 - 4 - 2019
  • Rome
    7 - 4 - 2019
    11 - 4 - 2019
  • Barcelona
    7 - 4 - 2019
    11 - 4 - 2019
  • Zurich
    7 - 4 - 2019
    11 - 4 - 2019
  • Istanbul
    14 - 4 - 2019
    18 - 4 - 2019
  • Bali
    14 - 4 - 2019
    18 - 4 - 2019
  • Singapore
    14 - 4 - 2019
    18 - 4 - 2019
  • Washington
    14 - 4 - 2019
    18 - 4 - 2019
  • London
    21 - 4 - 2019
    25 - 4 - 2019
  • Madrid
    21 - 4 - 2019
    25 - 4 - 2019
  • Munich
    21 - 4 - 2019
    25 - 4 - 2019
  • Berlin
    21 - 4 - 2019
    25 - 4 - 2019
  • New York
    21 - 4 - 2019
    25 - 4 - 2019
  • Istanbul
    12 - 5 - 2019
    16 - 5 - 2019
  • Bali
    12 - 5 - 2019
    16 - 5 - 2019
  • Singapore
    12 - 5 - 2019
    16 - 5 - 2019
  • Washington
    12 - 5 - 2019
    16 - 5 - 2019
  • Kuala Lumpur
    5 - 5 - 2019
    9 - 5 - 2019
  • Rome
    5 - 5 - 2019
    9 - 5 - 2019
  • Barcelona
    5 - 5 - 2019
    9 - 5 - 2019
  • Zurich
    5 - 5 - 2019
    9 - 5 - 2019
  • Dubai
    19 - 5 - 2019
    23 - 5 - 2019
  • Paris
    19 - 5 - 2019
    23 - 5 - 2019
  • Hong Kong
    19 - 5 - 2019
    23 - 5 - 2019
  • London
    26 - 5 - 2019
    30 - 5 - 2019
  • Madrid
    26 - 5 - 2019
    30 - 5 - 2019
  • Munich
    26 - 5 - 2019
    30 - 5 - 2019
  • Berlin
    26 - 5 - 2019
    30 - 5 - 2019
  • New York
    26 - 5 - 2019
    30 - 5 - 2019
  • Dubai
    9 - 6 - 2019
    13 - 6 - 2019
  • Paris
    9 - 6 - 2019
    13 - 6 - 2019
  • Hong Kong
    9 - 6 - 2019
    13 - 6 - 2019
  • Kuala Lumpur
    16 - 6 - 2019
    20 - 6 - 2019
  • Rome
    16 - 6 - 2019
    20 - 6 - 2019
  • Barcelona
    16 - 6 - 2019
    20 - 6 - 2019
  • Zurich
    16 - 6 - 2019
    20 - 6 - 2019
  • Istanbul
    23 - 6 - 2019
    27 - 6 - 2019
  • Bali
    23 - 6 - 2019
    27 - 6 - 2019
  • Singapore
    23 - 6 - 2019
    27 - 6 - 2019
  • Washington
    23 - 6 - 2019
    27 - 6 - 2019
  • London
    2 - 6 - 2019
    6 - 6 - 2019
  • Madrid
    2 - 6 - 2019
    6 - 6 - 2019
  • Munich
    2 - 6 - 2019
    6 - 6 - 2019
  • Berlin
    2 - 6 - 2019
    6 - 6 - 2019
  • New York
    2 - 6 - 2019
    6 - 6 - 2019
  • Istanbul
    7 - 7 - 2019
    11 - 7 - 2019
  • Bali
    7 - 7 - 2019
    11 - 7 - 2019
  • Singapore
    7 - 7 - 2019
    11 - 7 - 2019
  • Washington
    7 - 7 - 2019
    11 - 7 - 2019
  • Kuala Lumpur
    14 - 7 - 2019
    18 - 7 - 2019
  • Rome
    14 - 7 - 2019
    18 - 7 - 2019
  • Barcelona
    14 - 7 - 2019
    18 - 7 - 2019
  • Zurich
    14 - 7 - 2019
    18 - 7 - 2019
  • Kuala Lumpur
    21 - 7 - 2019
    25 - 7 - 2019
  • Rome
    21 - 7 - 2019
    25 - 7 - 2019
  • Barcelona
    21 - 7 - 2019
    25 - 7 - 2019
  • Zurich
    21 - 7 - 2019
    25 - 7 - 2019
  • London
    28 - 7 - 2019
    1 - 8 - 2019
  • Madrid
    28 - 7 - 2019
    1 - 8 - 2019
  • Munich
    28 - 7 - 2019
    1 - 8 - 2019
  • Berlin
    28 - 7 - 2019
    1 - 8 - 2019
  • New York
    28 - 7 - 2019
    1 - 8 - 2019
  • Dubai
    4 - 8 - 2019
    8 - 8 - 2019
  • Paris
    4 - 8 - 2019
    8 - 8 - 2019
  • Hong Kong
    4 - 8 - 2019
    8 - 8 - 2019
  • Kuala Lumpur
    11 - 8 - 2019
    15 - 8 - 2019
  • Rome
    11 - 8 - 2019
    15 - 8 - 2019
  • Barcelona
    11 - 8 - 2019
    15 - 8 - 2019
  • Zurich
    11 - 8 - 2019
    15 - 8 - 2019
  • Istanbul
    18 - 8 - 2019
    22 - 8 - 2019
  • Bali
    18 - 8 - 2019
    22 - 8 - 2019
  • Singapore
    18 - 8 - 2019
    22 - 8 - 2019
  • Washington
    18 - 8 - 2019
    22 - 8 - 2019
  • London
    25 - 8 - 2019
    29 - 8 - 2019
  • Madrid
    25 - 8 - 2019
    29 - 8 - 2019
  • Munich
    25 - 8 - 2019
    29 - 8 - 2019
  • Berlin
    25 - 8 - 2019
    29 - 8 - 2019
  • New York
    25 - 8 - 2019
    29 - 8 - 2019
  • Istanbul
    22 - 9 - 2019
    26 - 9 - 2019
  • Bali
    22 - 9 - 2019
    26 - 9 - 2019
  • Singapore
    22 - 9 - 2019
    26 - 9 - 2019
  • Washington
    22 - 9 - 2019
    26 - 9 - 2019
  • Kuala Lumpur
    1 - 9 - 2019
    5 - 9 - 2019
  • Rome
    1 - 9 - 2019
    5 - 9 - 2019
  • Barcelona
    1 - 9 - 2019
    5 - 9 - 2019
  • Zurich
    1 - 9 - 2019
    5 - 9 - 2019
  • Dubai
    8 - 9 - 2019
    12 - 9 - 2019
  • Paris
    8 - 9 - 2019
    12 - 9 - 2019
  • Hong Kong
    8 - 9 - 2019
    12 - 9 - 2019
  • London
    15 - 9 - 2019
    19 - 9 - 2019
  • Madrid
    15 - 9 - 2019
    19 - 9 - 2019
  • Munich
    15 - 9 - 2019
    19 - 9 - 2019
  • Berlin
    15 - 9 - 2019
    19 - 9 - 2019
  • New York
    15 - 9 - 2019
    19 - 9 - 2019
  • Dubai
    20 - 10 - 2019
    24 - 10 - 2019
  • Paris
    20 - 10 - 2019
    24 - 10 - 2019
  • Hong Kong
    20 - 10 - 2019
    24 - 10 - 2019
  • Kuala Lumpur
    27 - 10 - 2019
    31 - 10 - 2019
  • Rome
    27 - 10 - 2019
    31 - 10 - 2019
  • Barcelona
    27 - 10 - 2019
    31 - 10 - 2019
  • Zurich
    27 - 10 - 2019
    31 - 10 - 2019
  • Istanbul
    6 - 10 - 2019
    10 - 10 - 2019
  • Bali
    6 - 10 - 2019
    10 - 10 - 2019
  • Singapore
    6 - 10 - 2019
    10 - 10 - 2019
  • Washington
    6 - 10 - 2019
    10 - 10 - 2019
  • London
    13 - 10 - 2019
    17 - 10 - 2019
  • Madrid
    13 - 10 - 2019
    17 - 10 - 2019
  • Munich
    13 - 10 - 2019
    17 - 10 - 2019
  • Berlin
    13 - 10 - 2019
    17 - 10 - 2019
  • New York
    13 - 10 - 2019
    17 - 10 - 2019
  • Istanbul
    17 - 11 - 2019
    21 - 11 - 2019
  • Bali
    17 - 11 - 2019
    21 - 11 - 2019
  • Singapore
    17 - 11 - 2019
    21 - 11 - 2019
  • Washington
    17 - 11 - 2019
    21 - 11 - 2019
  • Kuala Lumpur
    24 - 11 - 2019
    28 - 11 - 2019
  • Rome
    24 - 11 - 2019
    28 - 11 - 2019
  • Barcelona
    24 - 11 - 2019
    28 - 11 - 2019
  • Zurich
    24 - 11 - 2019
    28 - 11 - 2019
  • Dubai
    3 - 11 - 2019
    7 - 11 - 2019
  • Paris
    3 - 11 - 2019
    7 - 11 - 2019
  • Hong Kong
    3 - 11 - 2019
    7 - 11 - 2019
  • London
    10 - 11 - 2019
    14 - 11 - 2019
  • Madrid
    10 - 11 - 2019
    14 - 11 - 2019
  • Munich
    10 - 11 - 2019
    14 - 11 - 2019
  • Berlin
    10 - 11 - 2019
    14 - 11 - 2019
  • New York
    10 - 11 - 2019
    14 - 11 - 2019
  • Dubai
    15 - 12 - 2019
    19 - 12 - 2019
  • Paris
    15 - 12 - 2019
    19 - 12 - 2019
  • Hong Kong
    15 - 12 - 2019
    19 - 12 - 2019
  • Kuala Lumpur
    22 - 12 - 2019
    26 - 12 - 2019
  • Rome
    22 - 12 - 2019
    26 - 12 - 2019
  • Barcelona
    22 - 12 - 2019
    26 - 12 - 2019
  • Zurich
    22 - 12 - 2019
    26 - 12 - 2019
  • Istanbul
    8 - 12 - 2019
    12 - 12 - 2019
  • Bali
    8 - 12 - 2019
    12 - 12 - 2019
  • Singapore
    8 - 12 - 2019
    12 - 12 - 2019
  • Washington
    8 - 12 - 2019
    12 - 12 - 2019
  • London
    1 - 12 - 2019
    5 - 12 - 2019
  • Madrid
    1 - 12 - 2019
    5 - 12 - 2019
  • Munich
    1 - 12 - 2019
    5 - 12 - 2019
  • Berlin
    1 - 12 - 2019
    5 - 12 - 2019
  • New York
    1 - 12 - 2019
    5 - 12 - 2019

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                                                   

This 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.

Objectives include:

  • 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.
  • To give delegates the ability to recognize which types of analysis are best suited to particular types of problems.
  • To give delegates sufficient background and theoretical knowledge to be able to judge when an applied technique will likely lead to incorrect conclusions.
  • 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.
  • To introduce some basic statistical methods and concepts.
  • To explore the use of Excel 2010 or 2013 for data analysis and the capabilities of the Data Analysis Tool Pack.

Content

The Basics

  • Sources of data, data sampling, data accuracy, data completeness, simple representations, dealing with practical issues.

Fundamental Statistics

  • Mean, average, median, mode, rank, variance, covariance, standard deviation, “lies, more lies and statistics”, compensations for small sample sizes, descriptive statistics, insensitive measures.

Basics of Data Mining and Representation

  • 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

  • Correlation analysis, the autocorrelation function, practical considerations of data set dimensionality, multivariate and non-linear correlation.

Histograms and Frequency of Occurrence

  • Histograms, Pareto analysis (sorted histogram), cumulative percentage analysis, the law of diminishing return, percentile analysis.

Frequency Analysis

  • The Fourier transform, periodic and a-periodic data, inverse transformation, practical implications of sample rate, dynamic range and amplitude resolution.

Regression Analysis and Curve Fitting

  • 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

  • Probability theory, properties of distributions, expected values, setting confidence limits, risk and uncertainty, ANOVA (analysis of variance).

Some more advanced ideas

  • Pivot tables, the Data Analysis Tool Pack, internet-based analysis tools, macros, dynamic spread sheets, sensitivity analysis.

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