Data Analytics

Course Overview

Harness Excel, SQL, and Tableau to drive powerful analysis and insights. Build confidence and credibility to apply this versatile skill set to countless jobs.

5 weeks

Online, Virtual, Onsite

Go from Zero to Fluent with Expert Guidance. Learn by getting first-hand help from world-class practitioners who use various Data analytics applications every day. Our instructors bring the latest techniques from the field straight to the classroom. Our curriculum emphasises real-world relevance and offers plenty of opportunity for practice through work-alongs, labs, and projects that mirror on-the-job applications.

Once you enroll, we equip you with our self-paced preparatory lessons to set you up for success. Dive into essential Data analytics concepts to gain a common vocabulary and start collaborating with classmates on day one.

Get guidance, feedback, and more from experts who are dedicated to supporting your learning and career goals. Instructors are on hand in class and during office hours to offer real-time support and help you turn ideas into action.

At Ehizua Hub, we are committed to helping people get affordable access to education and futureproof their career. Whether you want to level up or start a new career, we offer a range of flexible payment plans so you can achieve your goals today and pay at your own pace.

  • Installment payment
  • Full payment

We allow you settle with the payment plan of your choice, using different methods that will be made available to you both on our website and at our learning centre.

Once you begin the course, your instructor/mentor will ensure that all the key concepts are well understood before you move on to the next modules. This ensures that you develop the

confidence and skills needed to progress through the course. If you need additional support at any point, your instructor will provide 1:1 guidance to bring you up to speed.

What You will Learn

Milestone 1 Milestone 2
Data Framework Querying and organising data with SQL
Finding the right data Data narratives and visualisation with Tableau
ETL Basics Organizing data with functions (Use of VLOOKUP, HLOOKUP INDEX MATCH)
Data Cleaning and Aggregation with Excel Introduction to Microsoft Power BI
Milestone Project Milestone Project
Milestone 1 Milestone 2
Data Framework Querying and organising data with SQL
Finding the right data Data narratives and visualisation with Tableau
ETL Basics Organizing data with functions (Use of VLOOKUP, HLOOKUP INDEX MATCH)
Data Cleaning and Aggregation with Excel Introduction to Microsoft Power BI
Milestone Project Milestone Project

Career Prospect

Data analysis is one of the fast-growing fields that is in high demand. Those who venture into it have a long future of steady job growth ahead.  Our skilled data analysts are some of the most sought-after professionals in the world. Some of the areas you can function as a skilled data analyst include:

  • Business Intelligence Analyst
  • Data Analyst
  • Data Scientist
  • Data Engineer
  • Quantitative Analyst
  • Data Analytics Consultant
  • Operations Analyst
  • Marketing Analyst

Gain Vital Skills with Universal Relevance

Marketing managers who know SQL make 41% more than those who do not, and GMs earn 29% more with data analysis skills. Hone crucial proficiency in Excel, SQL, and Tableau and make career moves across industries and roles.

Tap Into a Valuable Professional Network

Let us help you form real connections that can change the course of your career. Meet practitioners and peers who can help you succeed through our global alumni network. Graduate with an industry-recognized certificate from Torrens University Australia and stand a chance to further your study in Australia.

Salary Range

Salaries for a cyber security analyst varies depending on the sector you work in, the type of employer (e.g., public, or private sector), your skills and experience, and your location. However, with your technical expertise in the profession, you are exposed to an average tentative salary range of N150,000 (lowest average) to N 350,000 (highest average).

Organizations to Work With

Data analysts can work in organisations of different sectors, both the public and private. With your acquired skills from our hub as a data analyst, you will be at an advantage in securing job roles available at companies across all sectors. Some of the areas you can function as a cyber data analyst include:

These are just a few examples of the types of organisations you could work for:

  • Information technology firms
  • Telecommunications companies
  • Professional services firms
  • Higher education institutions
  • Retail companies
  • Insurance companies
  • Pharmaceutical companies
  • Consultancy firms
  • Government parastatals.

Data Analysis is a promising career. Data analysts are found across variety of fields and are among those exploring the world today and their space is not limited to the above-listed. With your right combination of skills, you are certain to always find a space in the profession.

Course Fee

  • Onsite (Awoyaya Hub): N150,000 (One Hundred and Fifty Thousand Naira Only).
  • Live Virtual Training: N150,000 (One Hundred and Fifty Thousand Naira Only).
  • Online (Self-Paced Video learning): N70,000 (Seventy Thousand Naira Only).

Learning Objectives

  • Demonstrate knowledge of big data analytics.
  • Demonstrate the ability to think critically in making decisions based on data and deep analytics.
  • Demonstrate the ability to use technical skills in predicative and prescriptive modeling to support business decision-making.
  • Demonstrate the ability to translate data into clear, actionable insights.
  • Demonstrate effective communication skills that facilitate the effective presentation of analysis results.
  • Understand the key issues in big data management and its associated applications in intelligent business and scientific computing.
  • Acquire fundamental enabling techniques and scalable algorithms like Hadoop, Map Reduce and NO SQL in big data analytics.
  • Interpret business models and scientific computing paradigms and apply software tools for big data analytics.
  • Achieve adequate perspectives of big data analytics in various applications like recommender systems, social media applications etc.

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