Tag Archives: Big Data Analytics

6 Questions Organizations Should Ask About Big Data Architecture

Big data come with big promises, but businesses often face tough challenges to determine how to take big advantage of big data and deploy the effective architecture seamlessly into their system.

 

6 Questions Organizations Should Ask About Big Data Architecture

 

From descriptive statistics to AI to SAS predictive analytics – every single thing is spurred by big data innovation. At the 2017 Dell EMC World conference, which took place on Monday, the chief systems engineer for data analytics at Dell EMC, Cory Minton – gave a presentation simplifying the biggest decisions an organisation need to make when employing big data.

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Black Money in India Can be Traced With Ease by Applying Big Data Analytics

The economy took a hit with the recent demonetization of the INR 500 and 1000 currency notes. The jury of economists around the world are still debating whether the move was good or not, but it has definitely caused a huge inconvenience for the public. Moreover, exchanging such a large amount of old currency notes is nothing shy of a mammoth Herculean task, as almost 85 percent of the economy is in the form of high denomination currency.

Black Money in India Can be Traced With Ease by Applying Big Data Analytics

                Black Money in India Can be Traced With Ease by Applying Big Data Analytics

 

These measures have been taken by the government to curb the flow of Black Money in India and get rid of corruption from its roots. While there is still a mixed reaction from the common people about this move about it being good or bad, technological experts have a different viewpoint about preventing the flow of Black Money in the country.  They say that with use modern technologies like Big Data Analytics it will be possible to trace Black Money painlessly and with much ease.

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Why Getting a Big Data Certification Will Benefit Your Small Business

Do you know how much data is currently produced globally every year?

 

As per the reports published by IBM, the figures are 2.5 QB (Quintillion Bytes). The numeric representation of the same looks as: 2,500,000,000,000,000,000. And we thought that our mobile devices with 64GB memory space are capable of storing huge data.

 

Why Getting a Big Data Certification Will Benefit Your Small Business

 

Increasing reliance on Big Data

 

As technology is expanding at the speed next to light, more companies are planning to invest in Big Data platforms for getting the best out of it. Gartner Inc. had conducted a research recently among 437 global organisations across different industries and figured out that more than 75% of them are looking forward to the benefits they can derive from Big Data. The purpose for using Big Data varied to some instance across these organisations, however most of the companies were found to use data analytics for enhancing their customer service segments. Recently, security breach has hit the headline more often than global warming and that has been a factor of worry for many data driven companies. Thus, they are opting for Big Data tools in order to strengthen their online security.

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How do you Like your Coffee? Strong with a Lot of Numbers!?

How-do-you-like-your-coffee

 

In the health conscious world today, people are often engaging in hot debates as to which drinks have the most and least amounts of caffeine in them. But as data analysts we do not like to engage in any critical discussion without having a few graphs to show for our arguments! So, the moment someone put the kettle on, we turned on our computers to sip a cuppa and make a few caffeinated graphs.

The moment we head on to a cafe or a breakfast joint these days, we are bombarded with a long list of beverages which include an assortment of coffees, tea and other sugary drinks that promise to refresh our Monday-blues thirst with a shot of energizing elixir! It is not only spoiling to have so many options, but in fact confusing to say the least when the waiter/waitress keenly asks us how we would like our coffee.

But coffee, that is dubbed as the Devil’s juice (which I believe, further adds to its charm) is known to be bad for our health when drunk too much. So, we analysed and researched and downloaded some of the data of caffeine in various drinks like tea, soda and different blends of coffee pasted them on an Excel sheet and then used Proc Import to feed and read the data into SAS datasets.

The problem we faced next was that each category still had a few too many drinks to get a quick mental grasp on the matter (i.e. typically 100+). So, we took a two stage approach. The first thing we did was to plot just a handful of drinks in each of the categories which we then recognized as we have or want to drink, and then we plotted the entire list. The images of the small subset graphs are attached below:

 

1

Here’s a graph of caffeine content in the most popular coffees:

2

 

3

Here is the complete list of data for all coffees:

Drink

Fluid ounces

Caffeine

mg Caffeine

  (mg)per fluid oz
Nescafe Ice Java0.9100117.6
Stok Black Coffee Shots0.44090.9
Coffee Crave Fearless Black1284470.3
Chameleon Cold Brew Coffee32216067.5
Black Insomnia Coffee1270258.5
Death Wish Coffee1266055
Coffee (Espresso)1.57751.3
Killer Coffee8.543050.8
Biggby Espresso210050
Gourmesso Coffee Pods1.46548.1
Bizzy Cold Brew1675046.9
Peet’s Coffee Espresso1.57046.7
Nespresso Coffee Capsules1.46044.4
Robusta Coffee826533.1
Gloria Jean’s Coffee26733
Shock Coffee Triple Latte823128.9
Chameleon Cold Brew RTD Coffee1027027
Stumptown Cold Brew Coffee10.527926.6
Long Black615425.7
Greek Coffee (Metrios)25025
Turkish Coffee25025
Illy Issimo Cafe6.815522.8
Seattle’s Best Brewed Coffee1226021.7
Stumptown Cold Brew Chocolate + Milk1634021.2
Coffee Bean & Tea leaf Coffee1633320.8
Starbucks Grande Coffee1633020.6
Coffee (Brewed)816320.4
High Brew Coffee816320.4
Stumptown Cold Brew + Milk1631919.9
Starbucks Doubleshot6.512519.2
Caribou Brewed Coffee1630519.1
Black Medicine Iced Coffee1120618.7
TrueStart Performance Coffee5.19518.6
Costa Coffee15.227718.2
Bulletproof Coffee814518.1
Don Tomas Estate Coffee814518.1
Starbucks Via Ready Brew813516.9
Peet’s Brewed Coffee1626716.7
Gold Peak Coffee812615.8
Cafe Viva Probiotic Coffee812515.6
Dunkin’ Donuts Brewed Coffee1421015
K-Cup Coffee812015
Keurig Vue Pack1218015
Starbucks Grande Caffe Americano1622514.1
Starbucks Iced Espresso1622514.1
Starbucks Latte Macchiato1622514.1
Barista Bros Iced Coffee16.921913
Einstein Bros Coffee1620612.9
Americano Coffee1215412.8
Cappuccino1215412.8
Dutch Bros. Coffee2025612.8
Caffe Mocha1215212.7
Starbucks Protein and Coffee1114012.7
Biggby Brewed Coffee1620012.5
Starbucks Cold Brew Coffee1620012.5
Dunkin’ Donuts Iced Coffee2429712.4
Biggby Iced Coffee1619212
Panera Bread Coffee1618911.8
Pronto Coffee66711.2
Muscle Milk Coffee House1112010.9
Starbucks Grande Caffe Mocha1617510.9
Dunkin’ Donuts Latte1415110.8
Dunkin’ Donuts Mocha1415110.8
Vita Coco Cafe11.112010.8
Starbucks Discoveries Caffe Mocha50.753910.6
Starbucks Bottled Iced Coffee1111510.5
McDonalds (McCafe) Mocha1616710.4
Peet’s Caffe Mocha1616510.3
Peet’s Iced Mocha1616510.3
Tim Hortons Large Brewed Coffee2020010
Baskin Robbins Cappuccino Blast242349.8
Starbucks Doubleshot Energy + Coffee151459.7
Latte161549.6
Dare Iced Coffee16.91609.5
Starbucks Bottled Frappuccino9.5909.5
Peet’s Iced Coffee161509.4
Starbucks Grande Caffe Latte161509.4
Starbucks Grande Cappuccino161509.4
Flat White8.5779.1
McDonalds Coffee161459.1
McDonalds Iced Coffee222009.1
V Double Espresso Iced Coffee16.11479.1
Bean and Body Coffee8729
McDonalds (McCafe) Latte161428.9
Peet’s Caffe Americano161408.8
Peet’s Caffe Latte161408.8
Peet’s Cappuccino161408.8
Peet’s Iced Latte161408.8
Skinny Cow Iced Coffee8708.8
International Delight Iced Coffee8658.1
Starbucks Verismo Coffee Pods8607.5
Coffee (Instant)8577.1
Zola Coconut Water Espresso17.51257.1
Real Beanz Iced Coffee9.5666.9
Caffe Nero Coffee12806.7
Chick-fil-A Iced Coffee14946.7
Peet’s Decaf Espresso1.5106.7
Dunkin’ Donuts Iced Latte241516.3
Biggby Creamy Lattes161006.2
Biggby Frozen Lattes161006.2
Big Train Java Chip Ice Coffee8496.1
CoolBrew Coffee10606
Tim Hortons Small English Toffee Coffee10606
Tim Hortons Small French Vanilla Coffee10606
Dunkin’ Donuts Dunkaccino14835.9
Svelte Cappuccino Protein Shake11655.9
SlimFast Cappuccino Delight Shake10404
Choffy (roasted cacao)6233.8
Starbucks Refreshers16503.1
Indulgio Cappuccino8202.5
Starbucks Decaf Coffee16251.6
Coffee Leaf Tea8121.5
Dunkin’ Donuts Coolatta24180.8
Nescafe’ Ricoffy860.8
Arby’s Jamocha Shake16120.7
Coffee (Decaf, Brewed)860.7
Coffee (Decaf, Instant)830.3

Detailed data on all kinds of popular sodas:

DrinkFluid ouncesCaffeinemg Caffeine
(mg)per fluid oz
Bawls Exxtra161509.4
Blink Energy Water16.91508.9
Flatt Cola8658.1
Afri Cola12897.4
Fritz Kola11.2837.4
Premium Cola11.2837.4
Hansen’s Diet Red8.3576.9
Bawls10646.4
Bawls Orange10646.4
Bawls Cherry161006.2
Bawls Root Beer161006.2
Mountain Dew Game Fuel201216
Monster Mutant201155.8
Pepsi Max12695.8
Ski Soda12695.8
Sun Drop Soda12645.3
Mountain Dew Black Label16835.2
DOC 360201005
Mountain Dew Voltage12554.6
Diet Mountain Dew12544.5
Mountain Dew12544.5
Mountain Dew Baja Blast16724.5
Mountain Dew Live Wire12544.5
Pepsi One12544.5
Cult Cola16.9754.4
Surge Citrus Soda16694.3
Dr Pepper 1012514.2
Mello Yello12514.2
Mello Yello Zero12514.2
Starbucks Refreshers Canned12504.2
Cheerwine12484
Diet Cheerwine12484
Diet RC Cola12473.9
Diet Coke12463.8
Diet Coke Plus12453.8
Diet Coke with Lemon12453.8
Diet Coke with Lime12463.8
Diet Vanilla Coke12453.8
Hint Caffeine Kick Water16603.8
Soda Stream16603.8
TAB Diet Cola12453.8
Zevia Cola12453.8
RC Cola12433.6
RC Cola, Cherry12433.6
Shasta Cola12433.6
Diet Pepsi UK, AU, NZ12433.5
Diet Sunkist Orange Soda12423.5
Faygo Cola12423.5
Pepsi Max UK, NZ, AU12433.5
Diet Dr Pepper12413.4
Dr Pepper12413.4
Sunkist Orange Soda12413.4
Sunkist Sparkling Lemonade12413.4
Sunkist Ten20683.4
Diet Mr. Pibb12403.3
Honest Professor Fizz12403.3
Kickapoo Soda: Joy Juice & Fruit Shine12403.3
Pibb Xtra12403.3
Pibb Zero12403.3
Diet Dr Pepper Cherry12393.2
Diet Dr Pepper Cherry Vanilla12393.2
Diet Ruby Red Squirt12393.2
Diet Wild Cherry Pepsi12383.2
Dr Pepper Cherry12393.2
Dr Pepper Cherry Vanilla12393.2
Jazz Caramel Cream12383.2
Pepsi Cola12383.2
Pepsi Diet Lemon12383.2
Pepsi Diet Lime12383.2
Pepsi Diet Vanilla12383.2
Pepsi Throwback12383.2
Pepsi True7.5243.2
Ruby Red Squirt12393.2
TK Diet Cola12383.2
Wild Cherry Pepsi12383.2
Ale 8 112373.1
Crystal Pepsi20633.1
Inca Kola16503.1
Red Flash12373.1
Co-Operative Diet Cola16.9503
Double Cola12363
1893 Cola12342.8
Big Red Soda12342.8
Caffeinated Club Soda12342.8
Cherry Coke12342.8
Cherry Coke Zero12342.8
Coca-Cola Classic12342.8
Coke Zero12342.8
Diet Cherry Coca-Cola12342.8
Diet Coke with Splenda12342.8
Diet Pepsi12342.8
Vanilla Coke12342.8
Pepsi Next12322.7
Slurpee16402.5
A&W Cream Soda12292.4
Coca-Cola Life12282.3
Red Rock Cola12262.2
Barq’s Root Beer12221.8
Diet A&W Cream Soda12221.8
Pepsi Slurpee8141.8
Faygo Moon Mist12201.6
PC Cola Diet12131.1
PC Cola12121
Ritz Cola12100.9
Canada Dry Green Tea Ginger Ale1290.8
Boost Nutritional Drink850.6
7-Up1200
A&W Root Beer1200
Barq’s Red Creme Soda1200
Coca-Cola caffeine free1200
Diet Barq’s Root Beer1200
Fanta1200
Fresca1200
Ginger Ale or Ginger Beer1200
IBC Root Beer1200
Kinley Soda1200
Mug Root Beer1200
Orange Crush2000
Pepsi Caffeine Free1200
Sprite1200
Squirt Soda1200
Tonic Water11.900
Tropicana Twister Soda2000
Vernors Ginger Ale1200

While we are not too big a fan of the dancing bologna to be added into serious graphs, but in this we figured we would add a few minimalistic pictures of the drinks to make it easier to be distinguished.

Feel free to share how well your favourite drink fared in this very hotly debated list. And for more interesting data analysis news and Big Data courses stay tuned with DexLab Analytics. 

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The 1st Clinical Trial Predictive Model By Pfizer is Here

Joining the data analytics bandwagon, the pharmaceutical giant Pfizer has launched their first clinical trial predictive modelling system which is aimed at reducing study risk during protocol design and to better study execution phases. In a recent interview Jonathan Rowe, the Executive Director and Head of Clinical Development Quality Performance and Risk Management of Pfizer shed some light on these predictive modelling systems.

 

The 1st Clinical Trial Predictive Model By Pfizer is Here

 

When asked in the interview about the purpose of their predictive model and what it is meant to achieve, Rowe responded as follows…

 

It is true that there are quite a few models in the realm of GCP quality performance which we have developed and continue to refine. A relatively straightforward one is the correlation model where we correlate our clinical trial process performance to select the results of the GCP as is defined in the ICH E6.

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Credit Risk Managers Must use Big Data in These Three Ways

While the developed nations are slowly recovering from the financial chaos of post depression, the credit risk managers are facing growing default rates as household debts are increasing with almost no relief in sight. As per the reports of the International Finance which stated at the end of 2015 that household debts have risen to by USD 7.7 trillion since the year 2007. It now stands at the heart stopping amount of a massive USD 44 trillion and the amount of debts increased in the emerging markets is of USD 6.2 trillion. The household loans of emerging economies calculating as per adult rose by 120 percent over the period and are now summed up to USD 3000.

 

Credit risk managers must use Big Data in these three ways

 

To thrive in this market of increasing debts, credit risk managers must consider innovative methods to keep accuracy in check and decrease default rates. A good solution to this can be applying the data analytics to Big Data.

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The evolution of Big Data in business decision making

Big Data is big. We have all established that, and now we know that all the noise about Big Data is not just hype but is reality. The data generated on earth is doubling in every 1.2 years and the mountainous heap of data keep streaming in from different sources with the increase in technology.

 

The evolution of Big Data in business decision making

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How Data Scientists Take Their Coffee Every Morning

To a data scientist we are all sources of data, from the very moment we wake up in the morning to visit our local Starbucks (or any other local café) to get our morning coffee and swipe the screen of our tablets/iPads or smart phones to go through the big headlines for the day. With these few apparently simple regular exercises we are actually giving the data scientists more data which in-turn allows them to offer tailor-made news articles about things that interest us, and also prepares our favorite coffee blend ready for us to pick up every morning at the café.

How Data Scientists Have Their Coffee

The world of data science came to exist due to the growing need of drawing valuable information from data that is being collected every other day around the world. But is data science? Why is it necessary? A certified data scientist can be best described as a breed of experts who have in-depth knowledge in statistics, mathematics and computer science and use these skills to gather valuable insights form data. They often require innovative new solutions to address the various data problems.

As per estimates from the various job portals it is expected that around 3 million job positions are needed to be fulfilled by 2018 with individuals who have in-depth knowledge and expertise in the field of data analytics and can handle big data. Those who have already boarded the data analytics train are finding exciting new career prospects in this field with fast-paced growth opportunities. So, more and more individuals are looking to enhance their employability by acquiring a data science certification from a reputable institution. Age old programs are now being fast replaced by new comers in the field of data mining with software like R, SAS etc. Although SAS has been around in the world of data science for almost 40 years now, but it took time for it to really make a big splash in the industry. However, it is slowly emerging to be one the most in-demand programming languages these days.What a data science certification covers?

This course covers the topics that enable students to implement advanced analytics to big data. Usually a student after completion of this course acquires an understanding of model deployment, machine language, automation and analytical modeling. Moreover, a well-equipped course in data science helps students to fine-tune their communication skills as well.

Things a data scientist must know:

All data scientists must have good mathematical skills in topics like: linear algebra, multivariable calculus, Python and linear algebra. For those with strong backgrounds in linear algebra and multivariable calculus it will be easy to understand all probability, machine learning and statistics in no time, which is a requisite for the job.

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The Relationship between Big Data, Christmas and Santa

As a Big Data enthusiast, I look forward to data analytics playing a crucial role in the holiday season that is upon us. It is no exaggeration if we state that all sorts of people from CEOs to retailers to consumers will wile away the time crunching numbers this particular December.

The holiday season also is shopping for most consumers as, according to a report, no less than 25% of ecommerce transactions in the UK in last year i.e. 2014 were conducted in November and December. Companies face a transition from sales made from physical locations to those made online from desktops and laptops and mobile devices

The Relationship between Big Data, Christmas and Santa

  • Holiday Customers Lack in Loyalty

Loyalty takes the back seats as more and more buying choices are dictated by the capacity of the wallet. And when you have fifty vendors of repute to choose from while buying an item, the financial motive of savings prevails. Big Data lets businesses know the shopping days when their sales peaks.

All this highlights the need for personalization and how it makes them so much more likely to spend. In fact, according to studies personalization leads to 5 to 8 times increase on the return on investment in marketing and even improves sales by 10%. The report also stated that 56% of consumers made purchase decisions and the final purchase through computers. So, companies need to make the most of the data provided by companies like TIBC Spotfire and ShopperTrak.

  • Using Data in December

But the first question that comes to the mind about the use of Big Data during the period that shopaholics are at the peak of their activities, is why does it remain so underutilized. Tableau conducted a study that found that no less than 24% of all retailers based in the UK do not make effective use of data when the shopping season reaches its peak.

  • Use of Data by Consumers

Consumers also stand to gain when using it for the purposes of making purchase decisions. To cite a great example, we may consider the case of the WatsonTrend app. It analyzes data from ratings, comments, use of social media, reviews and other sources of data available on the net. The lists of the app are updated on a regular basis. The data and algorithms form the backbone of the app which may serve as real time shopping guides and even future trends may be predicted.

So, this Christmas shower you near and dear ones with gifts as enlightened consumers, Merry Christmas!

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Delimiters And Delimited Data in SAS

In this blog post we will delve into the world of delimiters as found in the SAS system of data analysis tools. Delimiters are an essential part of SAS without whose guidance SAS would be in some blind inspite of all the data that surrounds it as the data supplied to it either internally or as an external file.

 

sas courses

What are Delimiters?

Delimiters are essentially symbols to SAS that lets SAS know that the data is separate. They distinguish one set or category of data from others. This should give you an idea about how essential a part of data analytics, a delimiter plays.

How are the Delimiters Symbolized?

SAS accepts the following symbols and key strokes as delimiters:

  •  ,
  •  :
  • Tab
  •  ~
  • &
  •  –

How to Import Delimited Data?

This command imports data infile

Data claim_data;

infile datalines dlm = “,”;

Input sex $ name $ claim_amount ; datalines;

Male,Mahesh,15000

Male,Naveen,10000

Female,Neeta,18000

Male,Amit,7500

Female,Geeta,12000

;

run;

data claim_data ;

Infile E:\Project FT\SAS\Course Material\Class 1\Claim Data comma.txt’ dlm = “,”;

Input sex $ name $ claim_amount ;

Run;

What are the Functions of Delimiters?

An INFILE option, the DSD or delimiter-sensitive data serves varied functions. They are as follows:

  • The default delimiters are changed to wanted ones from the default blank.
  • In case a row contains two delimiters, SAS interprets that there is an instance of a case of missing value.
  •  Delimiters also strip the quotes within which character values are placed.

So the command would boil down to:

data claim_data ;

Infile E:\Project FT\SAS\Course Material\Class 1\Claim Data comma.txt’ dsd;

Input sex $ name $ claim_amount ;

Run

How to Read Data from an External CSV file?

Our next task is to read data from external CSV files. In order to do so we have to input the following:

proc import datafile = “E:\Project FT\SAS\Course Material\Class 1\exam_results.csv”

dbms = csv replace out = class_10_result; Getnames = yes; run;

In a Nutshell

What are Format, Informat and DSD?

  • Informat : This command instructs SAS how exactly to going about reading the data.
  • Format : This instructs SAS about the exact way in which to show the details.
  • DSD : This defines how data is separated by a delimiter.
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