Course Duration : Decision Making and Business Analytics in Practice
Course Duration : 1 Day Workshop Face-to-Face Instructor-led Workshop - Classroom
: Online workshop are delivered in two days, two units each day between 10:30 am to 1 pm and 3 pm to 5:30 pm
Course Fee : Available upon request (Write to us at info@tlcpak.com)
Course Location  : TLC (Karachi), Customer Onsite and Online
Course Code : TN211
Deliverables : Comprehensive Student Guide and Workshop Certificate

Customer onsite workshop can also be conducted for customers in Lahore, and Islamabad
ABOUT THIS WORKSHOP:
Interested in increasing your knowledge of the Big Data Analytics landscape? This course is for those who want expand their knowledge in the field of Big Data Analytics and the problems restricting them in developing their Big Data Analytics strategies. It is for those who want to become conversant with the terminology and the core concepts behind big data and analytics, applications, and systems. It is for those who want to start thinking about how Big Data Analytics can help their business to grow. It provides an introduction to one of the most common frameworks, Hadoop, that has made big data analysis easier and more accessible, increasing the potential for data to transform our world.

To improve the efficiency of the entire business, you need to take the emotion out of strategic decision-making and let data do the talking.

Explore a decision-making model and its process which individuals can follow or imitate to ensure they make the best choice among various options enabling them to design a solution by providing guidelines to help businesses reach a beneficial conclusion.

WORKSHOP OBJECTIVES:
At the end of this course, you will be able to:

  • Describe the Big Data landscape including examples of real world big data problems including the three key sources of Big Data: people, organizations, and sensors.
  • Explain the V’s of Big Data (volume, velocity, variety, veracity, valence, and value) and why each impacts data collection, monitoring, storage, analysis and reporting.
  • Get value out of Big Data by using a 7-step process to structure your analysis.
  • Identify what are and what are not big data problems and be able to recast big data problems as data science questions.
  • Provide an explanation of the architectural components and programming models used for scalable big data analysis.
  • Summarize the features and value of core Hadoop stack components.
  • This course can also be attended who are new to data science and want to expand their knowledge in the field of Big Data Analytics and want to see Big Data Analytics in Practice..
PREREQUISITES:
Participants attending this course should be familiar with basic Information Technology (IT) concepts and the role of general system wide infrastructure technologies and their applications. In short, you should be from a business or technical background to take up this course. No other specific prerequisite is required.

BY THE END OF THIS WORKSHOP:

  • The future of your business depends on the data and analytics capabilities you build and scale.

  • Critical components of Big Data and the role of IoT in Big Data, and Business Analytics.
  • Elaborating Cognitive Computing Framework.
  • Categorization of Analytical Methods and Models.
  • Leveraging data shall enable organizations to take full control of their business by understanding the past, the present, predicting and prescribing the future.
TARGET AUDIENCE:
  • Customers who want to build their knowledge in the space of Big Data Analytics and want to understand how to smartly tackle the challenges associated to decision making process.
  • CIO, CDO, CTO, Business and Technology Leaders, Data Analytics and Data Science personals, Data, Data Warehouse Engineers, Enterprise Architects, Project Managers, and all who want to equipped themselves with the foundational knowledge in the field of Big Data Analytics.
  • IT Consultants and Systems Integrators, Presales Technical individuals, and fresh graduates who want to start their career in the field of Big Data, Data Science, and Data Analytics.
ABOUT THE INSTRUCTOR
Training will be delivered by an experienced trainer with 25+ years of career experience imparting education and training services both locally and internationally and have served international enterprise technology vendors including IBM, Fujitsu, and ICL. Our instructor holds various industry professional certifications in the space of enterprise servers and storage technologies, Information Security, Enterprise Architecture, ITIL, Cloud, Virtualization, Green IT, and a co-author of 10 IBM Redboks and have deleloped 30+ courses in the field of Security and Digital technologies.

The training course flow will be a mix of lectures & classroom discussions so that participants can have a detailed understanding of various components of technologies causing digital disruption. 

COURSE OUTLINE 
Unit 1: Introduction to Big Data Technologies
  • Exponential Components of Data Growth –Some key facts and figures.
  • Understand how Technology is already being used.
  • A new style of emerging IT and Key contributors to Big Data.
  • Platform Sprawl -What is it?
  • Understanding Big Data and data exploration.
  • What does a Big Data platform do?
  • Types of Data Sources with in Data Center.
  • Understanding the types of Big Data.
  • Understanding Big Data 3Vs.
  • Analytics Breadth to Enable Decisions.
  • Describe Hadoop.
  • Understanding System of Records, Systems of Engagements, and Systems of Interactions.
  • Harnessing Big Data & Big Data Challenges.
  • High value Big Data Use Cases.
  • Big Data as a Service Market and Key market Players.
  • Unit 1 Assessment.


Unit 2: The Role of IoT in Big Data Analytics

  • What is Internet of Thing & Major components of IoT.
  • How are IoT and Big Data together beneficial for Organizations?
  • How IOT Works and example of an IoT system.
  • What are Sensor Based Data Acquisition Systems?
  • Understanding IoT Hub and IoT Gateway.
  • Internet of Things –Hardware & Software.
  • Basic Architecture of Internet of Things.
  • IoT –Embedded Operating System and Supported Platforms.
  • IoT in Banking – Enabling Banks’ Digital Future. 
  • IoT Use Cases – Shaping Banks’ Digital Future. 
  • IoT is the current wave of the Internet - Internet of Banking.
  • M2M Vs IoT –A Smart Comparison
  • IoT disadvantages that you should know.
  • IoT Market –Sizing the opportunity.
  • Emerging Standards supporting IoT.
  • Standard IoT Devices & Simple view of the IoT.
  • IoT Device Management and Use Cases.
  • IoT Applications.
  • Why most IoT projects are unsuccessful.
  • Unit 2 Assessment.
Unit 3: Exploiting the Role of Analytics in Business
  • Differentiating between analytics & business analytics.
  • Understanding Data Mining.
  • Eight main components of a typical Business Analytics dashboard.
  • Business Analytics vs Data Analytics.
  • Information Discovery and Visualization Environment.
  • Types of Analytics and why analytics matter.
  • Analytics mapping to the business applications.
  • Elaborating Cognitive Computing.
  • Cognitive Computing Framework.
  • A Categorization of Analytical Methods & Models.
  • How Analytics is used to enable decisions.
  • key benefits offered by Analytics.
  • Key areas that organizations wants optimizing through analytics.
  • Why is Big Data and Analytics are important?
  • Exploitation through the use of Big Data and Analytics that should be avoided.
  • The Analytical Life Cycle.
  • Use cases for big data analytics.
  • How can we make sense of Big Data and Analytics –The Data Science Process.
  • About the RProgramming Language.

  • Unit 3 Assessment.


Unit 4: Decision Making and Business Analytics in Practice

  • The importance of Dark Data in Big Data.
  • The use of analytical methods in business applications.
  • Decision Making –The High-level and Analytical process.
  • Exploring the types of Decision Making.
  • Business Analytics Defined.
  • The use of analytical methods in business applications.
  • The Spectrum of Business Analytics.
  • Decision-making methodologies.
  • Describe Decision Management.
  • Business Analytics in Practice: Financial Analytics, Human Resource Analytics, Marketing Analytics, Health Care Analytics, Supply Chain Analytics, Analytics for Government, and Web Analytics. 
  • Big Data and Analytics Platform –The Big Picture.
  • Using Analytics for better Decision-Making –Use Cases.
  • The 10 Best Data Analytics and BI Platforms/Tools in 2020.
  • Unit 4 Assessment.

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Following are the customers who have attended this workshop.
 

 
Group Photographs of students attended this Workshop

Packages Limited, A-Impakt International, ETSS, NBP and Emirates NBD Bank 
has attended a two day online workshop on "Decision Making and 
Business Analytics in Practice" on December 17 - 18, 2020.

Bank AL - Habib Limited has attended a two day online workshop on 
"Decision Making and Business Analytics in Practice" on July 14 - 15, 2021.

 

 

 
 
 
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