Big Data on Amazon Web Services


Duration: 3 Days

Program Level: Solution Architects and Solution Engineers

Online Option: Only – Open Enrolment.

Pre-requisites: Architecting on AWS, Developing on AWS, and Systems Operations on AWS.

Follow-on Certification: AWS Certified Data Analytics – Specialty

Course Dates:

Contact P2L to schedule the dates for this course.

Per Participant Pricing:
$2,400 CAD


AWS Big Data Cloud -This blue cloud seems to be teeming with nerve cells on a stark black field. It represents AWS Big Data at work.

Big Data on AWS

Master cloud-based big data solutions such as Amazon EMR, Amazon Redshift, Amazon Kinesis, create big data environments and leverage best practices to design big data environments for security and cost-effectiveness.

The importance of big data is that it lends itself to insightful analysis that results in cost reductions, time reductions, new product development, and optimized offerings, as well as smart decision making. Combining big data with proper analytics can facilitate business tasks such as:

  1. Pinpointing root causes of issues, defects, and failures.
  2. Recalculating risk portfolios quickly.
  3. Detecting fraud behavior before any damage is caused.

Big data technologies are almost necessary to organizations because traditional databases are no longer able to support the volumes, variety, and velocity of data.

If big data is not efficiently managed, organizations could face burgeoning costs and plummeting productivity. It is time for such organizations to migrate heavy current workloads onto big data technologies.

AWS Addressing Big Data challenges  

Big data technologies allow businesses to feasibly collect and store enormous datasets, as well as analyze those datasets to unravel valuable insights.

Collection of raw data: Logs, transactions, mobile devices among other things . A big data platform allows developers to absorb a wide variety of structured to unstructured data at any speed.

Storage: A scalable, secure, and durable repository for data.

Processing and analysis: Sorting, filtering, aggregating, and performing more advanced algorithms and functions. The resulting consumable data sets are stored for further processing and/or made available for consumption through data visualization and business intelligence tools.

Gain insights:  End-users may consume or view the resulting data as statistical predictions or recommended solutions.

Analytic Styles

Descriptive analytics answers the question: What happened and why?

Predictive analytics estimates the probability of a given event in the future.

Prescriptive analytics provide prescriptive actionable recommendations.

For more information, reference this AWS blog by Amazon as well as the P2L blog on Big Data by clicking here.


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