Big Data and Data Analytics
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Big Data and Data Analytics Course
Introduction:
In today's digital era, organizations across various industries require timely and insightful data to maintain their competitive edge. Big data serves as a transformative force that disrupts traditional decision-making approaches employed by organizational leaders. When harnessed effectively, big data offers precise business models and forecasts, enabling improved decision-making across all aspects of an organization. This course equips participants with the essential data literacy skills to stay efficient, effective, and ahead of the curve. Participants will gain knowledge on the rationale, applications, and implementation of technologies and methodologies, ranging from big data and Hadoop to data analytics and data science.
Course Objectives:
By the end of the training, participants will be able to:
- Illustrate the benefits, functionality, and ecosystem of big data
- Lead a big data initiative within their organization and generate organizational value by adopting data analytics
- Create well-rounded big data analytics teams by identifying the essential data professional roles
- Apply advanced analytics methodologies to optimize their line of business and solve complex business problems
- Leverage free, open-source applications and open data to deliver insights that generate an organizational competitive advantage
Who Should Attend?
This course is intended for working professionals who seek to use enterprise data to achieve better, more efficient business results and/or to make improved decisions through forecasting. This includes experienced data professionals such as Database Administrators, System Administrators, Business Analysts or Business Intelligence Specialists, as well as less technically-inclined management and administrative professionals.
Course Outlines:
The Big Data Landscape Introduction & Overview
- What is Big Data?
- Big data vs. its predecessors
- How big data relates to data analytics and data science
- The big data paradigm
- Big data professional roles
- How big data projects benefit businesses and industries
- The Hadoop ecosystem and architecture
- Other technologies in the big data paradigm
Big Data Project Planning
- Beyond the Hadoop ecosystem
- Other popular projects by MapR
- Commercial distributions of Hadoop
- Security within Hadoop
- Data engineering
- Useful programming languages
- The 4-step big data planning process
- Staying competitive as a big data professional
Advanced Analytical Methods for Problem-Solving
- The nature of data science and analytics
- Fraud prevention in real-time using machine learning
- Online sales improvement through recommendation engines
- Customer churn prediction and reduction through logistic regression
- Best option selection using multi-criteria decision making
- Stock price predictions using Markov Chains
- Analyzing how price changes impact sales volumes using simple linear regression
Basic Data Science Mechanics
- The benefits of object-oriented programming
- Programming Python
- R programming for data science
- Where is your data coming from?
- The traditional relational database management system (RDBMS – DSFD) source
- Structured Query Language (SQL) in analytics and data science
- Making the value of location data with Geographic Information System (GIS)
- Machine learning
- Popular machine learning algorithms
Free Resources to Analyze Data and Communicate Findings
- Free applications for data science and analytics
- Context and benchmarking using free and open data
- Scraping the web for market data
- The different types of data visualization
- Three simple steps to design for your audience
- Data graphics
- Design styles to convey powerful messages
- Design data analytics dashboards