Many organizations are working on big data to ensure business performance and increased productivity are apparent for the streamlining of business operations. This is vital in the business environment today as data increases and organizations are finding it cumbersome to manage it manually. To increase the awareness of how Big Data could be analyzed and effectively implemented, this training workshop looks at the several aspects of Big Data and its business impact and significance in measuring business success and performance
This Data Analytics To Monitor Organisatinal Preformance workshop is special because it highlights:
Data Analytics would most suited for CEOs and Managers, Financial and Data Analysts, Sales and Administration Managers, Systems Analysts and Engineers
DAY 1: 9:00AM – 5:00PM MODULE 1:
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Exercise: Channeling Your Inner Analyst - Participants are told to imagine receiving a memo from their supervisor explaining that the company is downsizing. They are expected to take on additional responsibilities including doing data analysis. They must rewrite their current job description to include the new data analyst duties
Facts or Feelings: Your Choice - As data becomes more widely available, businesses are finding more success in adopting a fact-based decision model rather than relying on traditional intuition alone. In this module, we examine more closely the two types of decision modelling businesses use as well as the benefits of the fact-based model. We cover the steps of the Rational Decision Model, a fact- based method for decision making.
MODULE 4:
Exercise: Who’s the Boss? – Participants are divided into groups; Imagine that they are the CEO of their own company. They define a business-related decision that they need to make and then apply the steps of the Rational Decision Model to arrive at the conclusion.
Big Data Anatomy - In this module, we visit the Big Data trend with a more detailed focus. We begin by defining the buzz word-"BIG DATA", examining its core attributes, and outlining the factors that contribute to data being 'big'. We explore how businesses collect structured and unstructured data, and the challenges they face in storing and effectively using both types of data.
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Exercise: Camp Data – Participants are asked to describe some of the big data challenges that their companies face and to outline what steps are being taken to address the problems.
Getting to Know Your Data - To better understand how to analyze data, we must first comprehend its depth. This requires drilling deep beneath the server it is located on and understanding its composition. Assume we are given a structured data set with labelled columns and completed rows. There are plenty of ways to summarize the story behind the data, but we cannot dive in without first getting to understand its fundamental structure. We begin by classifying the collected data as quantitative or qualitative. Then we further classify our column variables according to the way data is measured: nominal, ordinal, interval, or ratio. It is only after understanding this classification that we are able to proceed to the next step of choosing the appropriate analysis techniques which correspond to nominal, ordinal, interval or ratio variables.
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Exercise: Marketing to Low Renters – Participants are told to put on their data analyst thinking caps. They have been employed as a junior data analyst for a Marketing Company whose goal is to make a marketing campaign for a client who plans on targeting the 'needy' population. Participants are given a public housing data set and told to classify each variable according to its measurement.
Data Visualization - A picture is worth a thousand words, and there definitely is no exception when it comes to summarizing data. This module is dedicated to highlighting the importance of visualizing data, and how the human eye depends on visual representation to get a quick sense of data relevance. Visual representation is the audience's first impression of the data and forms a crucial step in inviting and maintaining genuine interest in a subject matter. We demonstrate how to create colorful, easy to understand tables, charts, and graphs that aid in helping us convey the story behind the data set being analyzed.
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Exercise: Table Mining – Participants develop tables to summarize trends in a data set related to low rent.
Exercise: Charting Poverty - Participants develop charts and graphs to summarize the poor housing epidemic in a public housing data set.
Numerical Data Summaries - Another way that data analysts summarize data is by providing a single number or summary statistic, that has meaning. This module explores how the mean, median, and mode can be used to summarize the centre of discrete and continuous grouped data. The range, standard deviation, and inter-quartile range measure the dispersion in the data set and provide information about how data points are spread.
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| Normal Fee | Early Bird | Group Fee |
|---|---|---|
| Sign up 1 pax | Sign up 1 pax | Sign up 3 pax or more |
| Pay 1 day(s) before course starts | Pay 14 day(s) before course starts | Pay 14 day(s) before course starts |
| MYR 3490 per pax | MYR 2890 per pax | MYR 2790 per pax |
| USD 1030 per pax | USD 850 per pax | USD 820 per pax |
(Fee inclusive of Buffet Lunch, Refreshment, Welcome Pack, Training Materials & Certificate of Achievement)
Upon successful completion of this program, you will receive a Certificate of Achievement.
Payment mode:
1. ONLINE PAYMENT by Credit card: You can opt to register and pay online with our latest payment integration system through our website.
2. BANK IN CHEQUE
Bank in and then scan the Bank-in slip and email to us before the course commence to confirm your seat.
Courier your cheque payment to our Finance HQ.
*Note that we DO NOT take any payments during the event.
3. BANK IN CASH:You can also pay by cash through bank-in our company bank account.
4. Telegraphic Transfer- You can also opt to use GIRO or telegraphic transfer of payment via international banks.
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Feel free to talk to us today, however most suitable for you.
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Office: +603 8074 9056
Email: info@itrainingexpert.com
Website: www.itrainingexpert.com
