Big Data Opens up Big Career Opportunities
Organizations across the world are exploring new opportunities by harnessing the power of data. The scale, speed, and variety of data being created today makes big data analytics professionals critical to these growing organizations. Here’s how you can get a head-start in this promising career with the right professional certification.

    IBM Big Data & Analytics Course
    A structured learning program designed by industry experts that provides:
  • Proficiency in C/C++, Java fundamentals, Python & Hadoop Fundamentals
  • Proficiency in Business Intelligence & Data Visualization
  • In-depth knowledge on Predictive Analytics and Predictive Modelling
  • Structured, hands-on understanding of Big Data Architecture & Big Data Security
  • Training on best practices for deploying Sectoral Analytics - HR/Marketing/Finance/Operational
  • Multiple projects across industries and functions to comprehensively test your skills and practical knowledge
  • Course materials and expert mentoring
    Must-have Skills
  • Knowledge and skills in data architecture
  • Applicable knowledge in coding and programming languages like Python, C/C++, Java
  • Knowledge and understanding of collecting business intelligence
    Industry Use Cases
  • Telecom companies use big data to perform location-based device analysis for revenue assurance. Price optimization, network expansion, and add-ons are also areas where telecom companies use big data to improve their business.
  • Healthcare organizations deploy big data to provide personalized treatment plans, predict patient admission patterns and optimize clinical research.
  • Financial services institutions use big data for customer analytics to personalize offers, as well as for algorithmic trading, risk assessment, fraud detection, and security threat detection.
  • Companies in retail, gaming and entertainment use big data to Increase customer conversion rates by improving targeted advertisement at a reduced customer acquisition cost

Career Avenues
Business Analyst

Role: Business users/knowledge workers; subject matter experts in the running of business
Competence: Needs self-service access to data and end-user analytics tools

Data Scientist
Role: Develop and deploy analytic models
Competence: Deep understanding of the mathematics of data, also known as quants

Application Developer
Role: Programmer who operationalizes repeatable analytics
Competence: Needs accurate sense of business requirements for analytic capabilities

Data Engineer
Role: Manages the data, builds physical and logical models
Competence: Responsible for the integration tasks to deploy capabilities defined by business needs

Chief Data Officer (CDO)
Role: Executive owner of the data, delegates the definition of logical business object models, governance rules, and data access policies to data engineers
Competence: Responsible for the quality of data and regulatory compliance


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