The Big Data Science Certified Professional (BDSCP) program from the Arcitura™ Big Data Science School is dedicated to excellence in the fields of Big Data science, analysis, analytics, business intelligence, technology architecture, design and development, as well as governance. A collection of courses establishes a set of vendor-neutral industry certifications with different areas of specialization. Founded by best-selling author, Thomas Erl, this curriculum enables IT professionals to develop real-world Big Data science proficiency. Because of the vendor-neutral focus of the course materials, the skills acquired by attaining certifications are applicable to any vendor or open-source platform. The Fundamental Big data course is part of this program and delivers a solid base of theory on what Big Data exactly is.
A Certified Big Data Science Professional has demonstrated proficiency in the analysis practices and technology concepts and mechanisms that comprise and are featured in contemporary Big Data environments and tools.
Knowledge of fundamental Big Data concepts and terminology is second nature to the Big Data Science Professional, as is an understanding of the business implications, benefits and challenges of adopting Big Data platforms and working with Big Data tools. Furthermore, the Big Data Science Professional must possess the ability to recognize appropriate analysis and analytics techniques and practices and to associate them with the correct problems and requirements, in addition to possessing a fundamental understanding of the underlying mechanics of Big Data technology platforms and mechanisms.
To achieve this certification, the following exams must be completed with a passing grade:
Exam B90.01: Fundamental Big Data
Exam B90.02: Big Data Analysis & Technology Concepts
Exam B90.03: Big Data Analysis & Technology Lab
Note that the Big Data Science Professional designation is based on vendor-neutral coverage of technologies and tools. Although vendor-specific examples of certain technologies are provided, none of the required exams, nor the attainment of the certification, require any knowledge or expertise in specific products. The purpose of this certification is to instill proven understanding and capabilities of common, foundational Big Data analysis and technology concepts, mechanisms, and considerations. This knowledge establishes a sound foundation that can be further built upon with additional training, accreditation and experience. Note that all certification requirements and course contents are reviewed regularly to stay in alignment with industry developments.
De training CloudSchool is bedoeld om inzicht te geven in de elementaire processen van Security & Cloud, en is daarom met name geschikt voor:
This course explores a range of the most relevant topics that pertain to contemporary analysis practices
technologies and tools for Big Data environments. The course content does not get into implementation or programming details
but instead keeps coverage at a conceptual level
focusing on topics that enable participants to develop a comprehensive understanding of the common analysis functions and features offered by Big Data solutions
as well as a high-level understanding of the back-end components that enable these functions.
De kennisdoelstelling is om de deelnemer de volgende onderwerpen te laten herkennen, beschrijven en toepassen:
- Fundamental Terminology and Concepts
- A Brief History of Big Data
- Business Drivers that Have Led to Big Data Innovations
- Characteristics of Big Data
- Benefits of Adopting Big Data
- Challenges and Limitations of Big Data
- Basic Big Data Analytics
- Big Data and Traditional Business Intelligence and Data Warehouses
- Big Data Visualization
- Common Adoption Issues
- Planning for Big Data Initiatives
- New Roles Introduced by Big Data Projects
- Emerging Trends
- Big Data Analysis Lifecycle (from business case evaluation to data analysis and visualization)
- A/B Testing, Correlation
- Regression, Heat Maps
- Time Series Analysis
- Network Analysis
- Spatial Data Analysis
- Classification, Clustering
- Outlier Detection
- Filtering (including collaborative filtering & content-based filtering)
- Natural Language Processing
- Sentiment Analysis, Text Analytics
- File Systems & Distributed File Systems, NoSQL
- Distributed & Parallel Data Processing,
- Processing Workloads, Clusters
- Cloud Computing & Big Data
- Foundational Big Data Technology Mechanisms
Big Data Science Professional certification
There are no prerequisites for this course. Some fundamental knowledge about computers is recommended.
3 dagen. De trainingsdagen duren van 10.00 uur tot 17.00 uur.
Module 1- Fundamental Big Data
This foundational course provides a high-level overview of essential Big Data topic areas. A basic understanding of Big Data from business and technology perspectives is provided, along with an overview of common benefits, challenges and adoption issues. The course content is divided into a series of modular sections, each of which is accompanied by one or more hands-on exercises.
Module 2 – Big Data Analysis & Technology Concepts
This course explores a range of the most relevant topics that pertain to contemporary analysis practices, technologies and tools for Big Data environments. The course content does not get into implementation or programming details, but instead keeps coverage at a conceptual level, focusing on topics that enable participants to develop a comprehensive understanding of the common analysis functions and features offered by Big Data solutions, as well as a high-level understanding of the back-end components that enable these functions.
Module 3 – Big Data Analysis & Technology Lab
This course module presents participants with a series of exercises and problems designed to test their ability to apply knowledge of topics covered previously in course modules 1 and 2. Completing this lab will help highlight areas that require further attention, and will further prove hands-on proficiency in Big Data analysis and technology and practices as they are applied and combined to solve real-world problems.
As a hands-on lab, this course provides a set of detailed exercises that require participants to solve a number of inter-related problems, with the goal of fostering a comprehensive understanding of how Big Data environments work from both front and back-ends, and how they are used to solve real-world analysis and analytics problems.
For instructor-led delivery of this lab course, the Certified Trainer works closely with participants to ensure that all exercises are carried out completely and accurately. Attendees can voluntarily have exercises reviewed and graded as part of the class completion. For individual completion of this course as part of the Module 3 Self-Study Kit, a number of supplements are provided to help participants carry out exercises with guidance and numerous resource references.
Trainingskosten: € 1800,-
Studiemateriaal: € 150,-
Examenkosten: € 500,-
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