big data analytics: challenge or opportunity?

<2013 BD Presentation> Copyright 2013 National University of Singapore. All Rights Reserved. 1

Big Data Analytics: Challenge or Opportunity?

Dr Carol Anne Hargreaves Institute of Systems Science National University of Singapore Email: [email protected]

August 2014


Volume Every day, 15 petabytes of new information are being generated. Data volume are expected to double every 2 years.

Velocity Data is coming at us faster and faster than ever before

Variety 80% of new data growth is from non-relational and non traditional data types like emails, documents, RFID feeds, multimedia etc

Data is Everywhere…What makes Big Data Challenging?

Veracity The messiness of the data (hash Tags, abbrev., typos, colloquial speech

Knowlege

<2013 BD Presentation> Copyright 2013 National University of Singapore. All Rights Reserved.

My smart phone tells me how many steps I have taken, the calories I have burnt each day as well as how well I have slept each night, etc. Many devices are now internet-enabled so that they self-generate and share data.

What is Big Data- Data is Everywhere…..

Companies and organisations are also keeping a digital record of everything that is going on: Just think of all the data generated daily in our financial systems, stock control systems, ordering systems, sales transaction systems


Data Engineering & Processing (Big Data Technologies)

(Hadoop, Hbase, MongoDB, SQL)

Data Driven

Decisions

Supports

Data Science/Business Analytics Data mining, Text Mining, Decision Trees, Neural Networks, Bayesian Networks

Business Knowledge

Application/Specific

Business Solutions

Recommendation Systems, Ad Placement Optimisation, Health Risk Systems

Business Problem

What is Big Data?.....................…..


Business Monitoring • Key Business Processes

• Business Intelligence ….Data Warehouses

Business Insights • Detailed Customer Transaction Data • External Unstructured Data (Internet, Emails) • Real time Data Access (Event happens, Analyse & Act)

Predictive Analytics • Score events most likely to happen • Location Situation Awareness • Recommendation Systems

Business Optimisation • Optimised Pricing Systems • Optimised Ad Serving • Optimised targeted Marketing Systems

What are the Big Data Opportunities? Big Data Big Opportunity

Data Cost Data Asset

Data Monetisation Smart Products

Business Insights User Experience


What are the Big Data Opportunities?

Big Data is being used to streamline its delivery routes and cut fuel costs. Vans are outfitted with sensors that monitor vehicle speed, location and more. By analyzing the GPS data as well as information from fuel-efficiency sensors, UPS cut its fuel consumption by 8.4 million gallons and cut 85 million miles off its routes in 2011.

Using Big data analytics doctors are better able to target and understand high risk CHF patients by utilizing natural language processing to extract key elements from unstructured History and Physical, Discharge Summaries, and Consult Notes.


Making the Most of Big Data….

Data Visualisation is the Key! A few charts with great data visualization are worth 1,000 slides. The key: reports should be easy to understand as well as recommend the next actionable step for business leaders.

Data Insights Action Measure


For example, we found 30 out of 500,000 customers who were at high risk of leaving. That's a small number, but the loss of those customers would have meant a loss of about $4 million dollars. If the company had waited for a completed data warehouse implementation, this insight would have been missed.

Use an Agile Approach for your Big Data Journey


Many businesses see data as costs, risks, and liabilities. Data is not seen as a source of value, but of additional work. What if nurses & doctors could remotely monitor patients through real time notifications based on pre-set thresholds set by the doctor, based on the patient’s condition.

Most healthcare professionals think data innovation means more work for them, not less, and takes away time from what they see as their key priorities in providing quality care.



BIG DATA consumes large space that wouldn't fit in the memory even with thousands of machines. And if it did, communication between those machines will block the network. Big data does not simply require big storage – it requires big smart storage.


The biggest challenge being faced as we enter the world of big data - we need to develop the people who will drive and implement useful big data systems. New storage systems must automatically and non-disruptively migrate data from one generation of a system to another to effectively address long-term


THE BIGGEST CHALLENGE for the use of “big data” is business knowledge, not technical. The challenge is figuring out how business people, both users, management and technical, will actually use data in practice.


Different users imagine data in very different ways. Understanding this key fact about data helps to understand why so-called “big data” solutions are so difficult to implement in practice.


Lack of Understanding - How to Apply Analytics to improve Business • Organisations want better ways to communicate complex

insights so they can quickly absorb the meaning of the data and take action.

• Leading organisation’s are now using data visualization as their first step in understanding their data and then process simulation.


3 – 5 Day Business Analytics Courses

MTech in Enterprise Business Analytics

Copyright 2013 National University of Singapore. All Rights Reserved.

Dr Carol Anne Hargreaves PhD (Statistics) University of South Africa. MBA University of Wales (Cardiff)

• Chief of Business Analytics Practice at ISS. Responsible for Consulting, Research & Teaching. Currently teaching – MTech (EBAC), NICF Customer Analytics, NICF Predictive Analytic NICF Statistics Bootcamp using R & Tableau & NICF Statistics for Business (2011-present)

• Prior to joining ISS, worked at Cegedim Strategic Data (CSD)(2009-2010) in Australia as a Quantitative Methods Manager. Provided primary and secondary market research analytics for client's in (customer profiling, target market segmentation, brand positioning,

competition, etc and was responsible for all quantitative research projects.

• In 2009, worked as a Statistical Modelling Analyst at Foxtel. Responsible for the Churn, Response, Acquisition Modelling.

• In 2005-2008, worked as an Advanced Analytics Statistician at Synovate Aztec in Australia. Developed models that enhanced the effectiveness of sales and marketing initiatives for clients

• In 2002-2005, worked as a Biostatistician at the National Health Medical Research Council (NHMRC) at the University of Sydney. Analyzed and reported on the status and results of various Cancer and Cardiovascular Clinical Trials.Advised on when a study should be stopped.

• In 1989-2002, while in South Africa, lectured statistics at several universities including the University of Durban - Westville and the University of Natal

mailto:[email protected]�

big data analytics: challenge or opportunity?

Technology

big data data

data volume

data innovation

gps data

data visualisation

velocity data

big data journey

big data opportunities