$1,000.00
If you’re completely new to big data and aren’t quite sure what it is, why it’s necessary, and how it works, then this is the course for you! We are going to clarify what big data is (and isn’t), while also defining some other related terms around data characterization and analysis methods. Then, we talk about some architectural problems with big data and how we solve them with cluster computing, distributed storage, and cluster management. Lastly, we will cover some of the popular technologies and illustrate how big data is used in the real world to hopefully shine a light on how big data is already impacting your daily life — whether you realize it or not. This training is designed to move participants from an initial understanding of Big Data terms and concepts to working with tool sets to dig into the data itself and start identifying the patterns and trends that would otherwise go unnoticed.
This course attests the following skills:
No prior knowledge or experience needed
After completing this course, students will be able to:
• Manipulate primitive data types in the R programming language using RStudio or Jupyter Notebooks.
• Control program flow with conditions and loops, write functions, perform character string and date operations, and generate regular expressions.
• Construct and manipulate R data structures, including vectors, factors, lists, and data frames.
• Read, write, and save data files and scrape web pages using R.
• How to perform operations in R including sorting, data wrangling using dplyr, and making plots
Module 1 – What is Big Data
• Characteristics of Big Data
• What are the V’s of Big Data?
• The Impact of Big Data
Module 2 – Big Data – Beyond the Hype
• Big Data Examples
• Sources of Big Data
• Big Data Adoption
Module 3 – The Big Data and Data Science
• The Big Data Platform
• Big Data and Data Science
• Skills for Data Scientists
• The Data Science Process
Module 4 – Big Data Use Cases
• Big Data Exploration
• The Enhanced 360 View of a Customer
• Security and Intelligence
• Operations Analysis
Module 5 – Processing Big Data
• Ecosystems of Big Data
• The Hadoop Framework
Click on the following link to see the current Course Schedule
Our minimum class-size is 3 for this course.
If there are no scheduled dates for this course, it can be customized to suit the time and skill needs of clients and it can be held online, at a rented location or at your premises.
Click on the following link below to arrange for a custom course: Enquire about a course date
Data is created constantly, and at an ever-increasing rate. Mobile phones, social media, imaging technologies to determine a medical diagnosis-all these and more create new data, and that must be stored somewhere for some purpose. Devices and sensors automatically generate diagnostic information that needs to be stored and processed in real time. Merely keeping up with this huge influx of data is difficult, but substantially more challenging is analyzing vast amounts of it, especially when it does not conform to traditional notions of data structure, to identify meaningful patterns and extract useful information. These challenges of the data deluge present the opportunity to transform business, government, science, and everyday life.
“Big Data” is data whose scale, diversity and complexity require new architecture, techniques, algorithms, and analytics to manage it and extract value and hidden knowledge from.
Although the volume of Big Data tends to attract the most attention, generally the variety and velocity of the data provide a more apt definition of Big Data. (Big Data is sometimes described as having 4 Vs: volume, variety, veracity and velocity.)
Due to its size or structure, Big Data cannot be efficiently analyzed using only traditional databases or methods. Big Data problems require new tools and technologies to store, manage, and realize business benefits from the following types of data:
Big Data professionals use data analytics lifecycle which consists of six stages
CERTFICATE OF COMPLETION: Participants will receive a certificate of completion at the end of a course. This is not an official certification for the product and/or software. Our courses do indicate the appropriate certification exam(s) that the participant can sit. Data Vision Systems does not provide certification or deliver the certification exams. Participants are responsible for arranging and paying for the certification exams on the appropriate certification body.
CANCELLATION POLICY: There is never a fee for cancelling seven business days before a class for any reason. Data Vision Systems reserves the right to cancel any course due to insufficient registration or other extenuating circumstances. Participants will be advised prior to doing so
.
Reviews
There are no reviews yet.