Big Data

Data Storytelling is suited towards any professionals that work with data and charts. If you need to tell better stories with your data, then this course is for you. The curriculum challenges participants to communicate effective and impactful data-driven narratives, focusing on principles of effective data storytelling.

Delivery Method and Programmes Offered

You can choose any method of learning that you want.

Virtual Instructor-Led Training(VILT) Programmes

Online trainings conducted via Zoom led by an Instructor.

The first day of training introduces the domain of Big Data, the drivers for advanced analytics, and the role of the data scientist, analytic project lifecycle designed for the particular characteristics and challenges of hypothesis-driven analysis with Big Data. The second day training learn to examine fundamental statistical techniques in the context of the open source analytic software environment. The second day also highlights the importance of exploratory data analysis via visualizations and reviews the key notions of hypothesis development and testing with discuss a range of advanced analytical methods, including clustering, classification, regression analysis, time series and text analysis. The third day more into interpret data into visualization. Data Storytelling is suited towards any professionals that work with data and charts. If you need to tell better stories with your data, then this course is for you. The curriculum challenges participants to communicate effective and impactful data-driven narratives, focusing on principles of effective data storytelling.
This training provides a practitioner’s approach to some of the key techniques and tools used in Big Data analytics. Knowledge of these methods will help people become active contributors to Big Data analytics projects. The training content is designed to assist multiple stakeholders: business and data analysts looking to add Big Data analytics skills to their portfolio; database professionals and managers of business intelligence, analytics, or Big Data groups looking to enrich their analytic skills; and college graduates investigating data science as a career field. Based on the assessment of exercise CCSD will award a certification to the participant.
  • Software Engineers
  • Application Developers
  • IT Architects
  • System administrators
  • Data Analysts
  • DAY 1
  • Big Data Overview
  • Data Structures
  • Analyst Perspective on Data Repositories
  • Current Analytical Architecture
  • Drivers of Big Data
  • Emerging Big Data Ecosystem and a New Approach to Analytics
  • Data Analytics Lifecycle Overview
  • Marketing Analytics
  • DAY 2
  • Monitoring Performance through Effective Planning and Reporting Techniques using Big Data Analytical
  • Stakeholder Management using – Data Management Technique
  • Data Preparation
  • Learning About the Data
  • Data Conditioning
  • Visualize
  • Common Tools for the Data Preparation Phase
  • DAY 3
  • Why Data Storytelling
  • Explore or explain
  • Who, What, How
  • Insights & The Big Idea
  • Storyboarding
  • Graphical Integrity
  • Graphical Perception
  • Choosing a Visual
  • Gestalt Principles of Visual Grouping
  • Story Points
  • PROGRAMME DATES (You can choose to attend either one)

    First Session
    10, 11 & 12 September 2021
    Second Session
    8, 9 & 10 October 2021
    Third Session
    5, 6 & 7 November 2021
    Fourth Session
    3, 4 & 5 December 2021

    Self Paced Learning(SPL) Programmes

    Video based online learning that you learn on your own time & schedule.
    3 levels you can choose from: Beginner, Intermediate, and Advance.

    This Big Data Hadoop Certification course is designed to give you an in-depth knowledge of the big data framework using Hadoop and Spark. In this hands-on big data course, you will execute real-life, industry-based projects using integrated labs.

  • Analytics professionals
  • Testing and mainframe professionals
  • Business intelligence professionals
  • Graduates looking to begin a career in big data analytics
  • Senior IT professionals
  • Data management professionals
  • Project managers
  • Learn how to navigate the Hadoop ecosystem and understand how to optimize its use
  • Implement partitioning, bucketing, and indexing in Hive
  • Process real-time streaming data
  • Implement User-Defined Functions (UDF) and User-Defined Attribute Functions (UDAF) in Spark
  • Ingest data using Sqoop, Flume, and Kafka.
  • Work with RDD in Apache Spark
  • Perform DataFrame operations in Spark using SQL queries
  • Lesson 01 – Introduction to Bigdata and Hadoop
  • Lesson 02 – Hadoop Architecture Distributed Storage (HDFS) and YARN
  • Lesson 03 – Data Ingestion into Big Data Systems and ETL
  • Lesson 04 – Distributed Processing MapReduce Framework and Pig
  • Lesson 05 – Apache Hive
  • Lesson 06 – NoSQL Databases HBase
  • Lesson 07 – Basics of Functional Programming and Scala
  • Lesson 08 – Apache Spark Next-Generation Big Data Framework
  • Lesson 09 – Spark Core Processing RDD
  • Lesson 10 – Spark SQL Processing DataFrames
  • Lesson 11 – Spark MLib Modelling BigData with Spark
  • Lesson 12 – Stream Processing Frameworks and Spark Streaming
  • Lesson 13 – Spark GraphX
  • This MongoDB certification course will help you master the concepts of MongoDB development services, the most popular NoSQL database. You will learn how to handle data storage, data modeling, ingestion, query, sharding, and data replication with MongoDB, along with installing, updating, and maintaining the MongoDB environment. You will also learn MongoDB configuration and backup methods, monitoring, and operational strategies. You will be career-ready as a MongoDB professional upon completion.
    This MongoDB Certification course is ideal for professionals aspiring to launch a career in NoSQL databases and MongoDB, including database administrators, database architects, software developers, software architects, database professionals, project managers, IT developers, testers, analytics professionals, research professionals, and system administrators.
  • Develop expertise writing Java and NodeJS applications using MongoDB
  • Get hands-on experience creating and managing different types of indexes in MongoDB for query execution
  • Gain proficiency in MongoDB configuration, backup methods, monitoring, and operational strategies
  • Master the skills of replication and sharding of data in MongoDB to optimize read/write performance and perform installation, configuration, and maintenance of the MongoDB environment
  • Proficiently store unstructured data in MongoDB and develop skills for processing huge amounts of data using MongoDB tools
  • Acquire an in-depth understanding of how to manage DB Notes, Replica set, and master-slave concepts
  • Lesson 01 – NoSQL Database Introduction
  • Lesson 02 – MongoDB – A Database for the Modern Web
  • Lesson 03 – CRUD Operations in MongoDB
  • Lesson 04 – Indexing and Aggregation
  • Lesson 05 – Replication and Sharding
  • Lesson 06 – Developing Java and Node JS Application with MongoDB
  • Lesson 07 – Administration of MongoDB Cluster Operations
  • This Tableau course teaches you how to build visualizations, organize data, and design dashboards to empower more meaningful business decisions. You’ll be exposed to the concepts of statistics, data mapping, and establishing data connections and be prepared for the Tableau Desktop 10 Qualified Associate exam.
  • Analytics professionals
  • Data analysts
  • BI and reporting professionals
  • IT developers and testers
  • Data scientists
  • Project managers
  • Grasp the concepts of Tableau Desktop 10, become proficient with Tableau statistics, and build interactive dashboards
  • Master arithmetic, logical, table, and LOD calculations and ad-hoc analytics
  • Learn to analyze data using Tableau Desktop as well as clustering and forecasting techniques
  • Master special field types and Tableau-generated fields and the process of creating and using parameters
  • Master data sources and datable blending, create data extracts, and organize and format data
  • Become an expert on visualization techniques such as heat map, tree map, waterfall, Pareto, Gantt chart, and market basket analysis
  • Become an expert on visualization techniques such as heat map, tree map, waterfall, Pareto, Gantt chart, and market basket analysis
  • Learn how to build interactive dashboards, story interfaces, and how to share your work
  • Lesson 01 – Getting Started with Tableau
  • Lesson 02 – Working with Tableau
  • Lesson 03 – Deep diving with Data and Connections
  • Lesson 04 – Creating Charts
  • Lesson 05 – Adding calculation to your workbook
  • Lesson 06 – Mapping data in Tableau
  • Lesson 07 – Dashboard and Stories
  • Lesson 08 – Visualizations For An Audience
  • This Power BI training course will help you get the most out of Microsoft’s Power BI, a suite of tools that lets you build interactive dashboards for analyzing data and extracting business insights. This course will help you master the development of dashboards from published reports, discover greater insights from your data with Quick Insights, and learn practical applications for Power BI tasks, such as gathering and analyzing data. You will also learn valuable Power BI troubleshooting tips.
    This Power BI course is ideal for people who want to understand how to use Power BI tools and create customized visuals with Power BI developer tools. It is also suitable for business intelligence (BI) and reporting professionals, data analysts, and professionals working with data in any sector.
  • Understand Power BI concepts like Microsoft Power BI desktop layouts, BI reports, dashboards, and Power BI DAX commands and functions
  • Learn how to experiment, fix, prepare and present data quickly and easily
  • Form relationships in your data model and learn data visualization best practices
  • Gain a competitive edge in creating customized visuals and deliver a reliable analysis of vast amount of data using Power BI
  • Create a sales analysis report and a project management report
  • Lesson 01 – Get And Prep Data Like A Super Nerd
  • Lesson 02 – Develop Your Data Nerd Prowess
  • Lesson 03 – Developing Reports And Dashboards
  • Lesson 04 – Tips, Tricks, And Capstone Project
  • In this Big Data on AWS course, you will become familiar with the concepts of cloud computing and its deployment models. You’ll learn about the Amazon Web Services (AWS) cloud platform, Kinesis Analytics, AWS big data storage, processing, analysis, visualisation and security services, EMR, AWS Lambda and glue, machine learning algorithms, and much more.
    Data scientists Solutions architects Data engineers Data analysts
  • Understand how to use Amazon EMR for processing the data using Hadoop ecosystem tools
  • Analyze and transform big data using Kinesis Streams
  • Understand how to use Amazon Kinesis for big data processing in real-time
  • Visualize data and perform queries using Amazon QuickSight
  • Lesson 01 – Get And Prep Data Like A Super Nerd
  • Lesson 02 – Develop Your Data Nerd Prowess
  • Lesson 03 – Developing Reports And Dashboards
  • Lesson 04 – Tips, Tricks, And Capstone Project
  • This data analytics course provides fundamental concepts of data analytics through real- world case studies and examples and gives insights into how to apply data and analytics principles in your business. You’ll learn about project lifecycles, the difference between data analytics, data science, and machine learning; building an analytics framework, and using analytics tools to draw business insights.
    This course is ideal for anyone who wishes to learn the fundamentals of data analytics and pursue a career in this growing field. The course also caters to CxO-level and middle management professionals who want to improve their ability to derive business value and ROI from analytics.
    li>Understand how to solve analytical problems in real-world scenarios
  • Work with different types of data
  • Understand charts, graphs, and tools used for analytics and use them to gain valuable insights
  • Define effective objectives for analytics projects
  • Understand the importance of data visualization to drive more effective business decisions and ROI
  • Create an analytics adoption framework Identify upcoming trends in data analytics
  • Lesson 01 – Data Analytics Overview
  • Lesson 02 – Dealing with Different Types of Data
  • Lesson 03 – Data Visualization for Decision making
  • Lesson 04 – Data Science Data Analytics and Machine Learning
  • Lesson 05 – Data Science Methodology
  • Lesson 06 – Data Analytics in Different Sectors
  • Lesson 07 – Analytics Framework and Latest trends
  • Become an expert in data analytics using the R programming language in this data science certification training course. You’ll master data exploration, data visualization, predictive analytics and descriptive analytics techniques with the R language. With this data science course, you’ll get hands-on practice by implementing various real-life, industry-based projects in the domains of healthcare, retail, insurance, and many more.
    There is an increasing demand for skilled data scientists across all industries, making this data science certification course well-suited for participants at all levels of experience. We recommend this Data Science training particularly for the following professionals:
  • IT professionals
  • Software Developers
  • Analytics professionals
  • Gain a foundational understanding of business analytics
  • Master R programming and understand how various statements are executed in R
  • Define, understand and use the various apply functions and DPYR functions
  • Gain a basic understanding of various statistical concepts
  • Understand and use linear, non-linear regression models, and classification techniques for data analysis
  • Learn and use clustering methods including K-means, DBSCAN, and hierarchical clustering
  • Install R, R-studio, and workspace setup, and learn about the various R packages
  • Gain an in-depth understanding of data structure used in R and learn to import/export data in R
  • Understand and use the various graphics in R for data visualization
  • Understand and use hypothesis testing method to drive business decisions
  • Learn and use the various association rules and Apriori algorithm
  • Lesson 1: Introduction to Business Analytics
  • Lesson 2: Introduction to R Programming
  • Lesson 3: Data Structures
  • Lesson 4: Data Visualisation
  • Lesson 5: Statistics for Data Science-I
  • Lesson 6: Statistics for Data Science-II
  • Lesson 7: Regression Analysis
  • Lesson 8: Classification
  • Lesson 9: Clustering
  • Lesson 10: Association
  • Establish your mastery of data science and analytics techniques using Python by enrolling in this Data Science with Python course. You’ll learn the essential concepts of Python programming and gain in-depth knowledge of data analytics, machine learning, data visualization, web scraping, and natural language processing. Python is a required skill for many data science positions, so jumpstart your career with this interactive, hands-on, Data Science with Python course.
  • Analytics professionals willing to work with Python
  • Anyone with a genuine interest in data science
  • Software and IT professionals interested in analytics
  • Gain an in-depth understanding of data science processes, data wrangling, data exploration, data visualization, hypothesis building, and testing; and the basics of statistics
  • Perform high-level mathematical computations using the NumPy and SciPy packages and their large library of mathematical functions
  • Gain an in-depth understanding of supervised learning and unsupervised learning models such as linear regression, logistic regression, clustering, dimensionality reduction, K-NN, and pipeline
  • Understand the essential concepts of Python programming such as datatypes, tuples, lists, dicts, basic operators, and functions
  • Perform data analysis and manipulation using data structures and tools provided in the Pandas package
  • Use the Scikit-Learn package for natural language processing and matplotlib library of Python for data visualization
  • Lesson 00 – Course Overview
  • Lesson 01 – Data Science Overview
  • Lesson 02 – Data Analytics Overview
  • Lesson 03 – Statistical Analysis and Business Applications
  • Lesson 04 – Python Environment Setup and Essentials
  • Lesson 05 – Mathematical Computing with Python (NumPy)
  • Lesson 06 – Scientific computing with Python (SciPy)
  • Lesson 07 – Data Manipulation with Pandas
  • Lesson 08 – Machine Learning with Scikit–Learn
  • Lesson 09 – Natural Language Processing with Scikit Learn
  • Lesson 10 – Data Visualization in Python using matplotlib
  • Lesson 11 – Web Scraping with BeautifulSoup
  • Lesson 12 – Python integration with Hadoop MapReduce and Spark
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