For many, it's a nebulous term that invokes images of huge server farms humming away. Or perhaps you think of receiving some kind of personalized advertisement from a retailer. But big data is so much deeper and broader than that. Read this post to know more http://www.lanterninstitute.ca

1. Things You Need to Know
about
Big Data

2. Simply put, Big Data refers to large data sets that are
computationally analysed to reveal patterns and trends
relating to a certain aspect of the data. There’s no minimum
amount of data needed for it to be categorised as Big Data, as
long as there’s enough to draw solid conclusions.
M-Brain explains the different facets of Big Data through the 8
V’s..

3. Big Data is available in an endless
number of places and it’s only
increasing as time goes on. A
simple Google search will enable
you to find a data repository for
just about everything. A lot of
people aren’t aware of just how
much data is already available for
access and analysis.
How Can You Access Big Data?

4. How you can access
and utilise this data
can be split into six
parts:
Data Extraction
Before anything happens, some data is
needed. This can be gained in a number
of ways, normally via an API call to a
company’s web service.
Data Storage
The main difficulty with Big Data is managing
how it will be stored. It all depends on the
budget and expertise of the individual
responsible for setting up the data storage as
most providers will require some programming
knowledge to implement.

5. Like it or not, data sets come in all shapes and
sizes. Before you can even think about how the
data will be stored, you need to make sure it is
in a clean and acceptable format.
Data Cleaning
Data mining is the process of discovering
insights within a database. The aim of this is to
provide predictions and make decisions based on
the data currently held.
Data Mining

6. Perhaps the most important is the visualisation of the
data. This is the part that takes all the work done prior
and outputs a visualisation that ideally anyone can
understand. This can be done using programming
languages such as Plot.ly and d3.js or software such as
Tableau.
Data Analysis
Data Visualisation
Once all the data has been collected it needs to be
analysed to look for interesting patterns and trends. A
good data analyst will spot something out of the
ordinary, or something that hasn’t been reported by
anyone else.

7. How Do You Learn More?
Big Data is a broad subject, so learning it all requires knowledge of
several areas. Someone looking to work in the field would need an
array of certain skills, including one or more of the following:
A knowledge of a programming language that relates to data
analysis, namely R, Python, SAS or SQL
A good understanding of Maths and Statistics
Experience on how to scrape a webpage
Basic Excel skills

8. Are there careers related to Big Data?
With the growing access to Big Data, it should
come as no surprise that the volume of careers
related is on the rise as well. According to the
Data Motion, a Big Data Engineer would earn
an average salary of $150,000 a year.

9. actualusesof
bigdata
0 8 S I N A I D E S I G N E R S
Netflix’s well known Hadoop data processing platform.
Cloud architecture is highly scalable and allows Neflix to
quickly provision computing resources as its sees the need.
Traffic patterns are analysed across device types and
localities to help improve the reliability of video streaming
and plan for growth.The technology is also used for
Netflix’s recommendation engine based on a customer’s
viewing habits and stated preferences.
Netflix

10. WeatherSignal works by repurposing the sensors in Android
devices to map atmospheric readings. Handsets such as the
Samsun S4, contain a barometer, hygrometer (humidity), ambient
thermometer and lightmeter.
Obviously, the prospect of millions of personal weather stations
feeding into one machine that will average out readings is exciting,
and one that has the potential to improve forecasting.il Habits
Weather

11. Heart Disease
IBM is predicting heart disease with big data. Analysis of electronic
health record data could reveal symptoms at earlier stages than
previously.
IBM uses the Apache Unstructured Information Management
Architecture (UIMA) to extract the known signs and symptoms of
heart failure from available text.
With no single strong indicator, only weak signals or ‘co-
morbidities’, such as hypertension, diabetes, associated medications,
ECG and genomic data etc. can be analysed.

12. Infectious diseases
Again IBM, this Venture Beat article looks at a model and data
from the World Health Organization. IBM looked at local climate
and temperature to find correlations with how malaria spreads.
This analysis is used to predict the location of future outbreaks.
The Spatio Temporal Epidemiological Modeler (STEM) is free and
open source.

13. Doctor performance
Crimson is a system that shows variables
including complications, hospital readmissions
and measures of cost. It colour codes signals as
to how well a doctor is performing against his or
her peers.

14. Contact Us
112 College Street, Suite 411
Toronto, ON
Canada M5G 1L6
contact@lanterninstitute.ca
Phone: 1-800-647-0526
http://www.lanterninstitute.ca

15. Thank You