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Here is The Data Why We Think Iphone 7 is Going to Be a Huge Hit

Posted on September 5, 2016May 23, 2020 by Dexlab

While the media and the tech analysts think that they have got the iPhone 7 all figured out and presume that the iPhone 7 sales will not be much as it is not offering much of an improvement from the previously launched iPhone 6S. But we have taken a look at the data and have a theory that tells a different story. Why?

We think that iPhone 7 is going to be a massive hit because Apple Inc. Is installing its largest ever iPhone user base which is more than two years old.

Here is chart that depicts how many people upgrade their phones to the latest model soon after its launch. We discovered that the switch is highly dependent on the fact of how old their previous phones were. Surprisingly only 17 percent of the people change their phones immediately after the launch of a new one. The people who change their phones immediately after the launch of a new release is the lot with “the next gen phone + 1” or people with phones that are two years or older!

Refer to the infographic below to understand the iPhone switching factor:

Continue reading “Here is The Data Why We Think Iphone 7 is Going to Be a Huge Hit”

We Analyzed The Statistics Of Game Of Thrones

Posted on June 29, 2016June 29, 2016 by Dexlab

Are you a data science enthusiast as well as a fan of Game of Thrones? Then this blog is where you should stick your eyes to and fear not as we will not give you any spoilers.

Of the zillion of characters in the show, ever imagined which is the main character the show is leading with? Amidst the characters like Tyrion, Bran, Dany and pals who is the main one in the Game of Thrones? Continue reading “We Analyzed The Statistics Of Game Of Thrones”

Infographic: List of Our Courses from Dexlab Analytics

Posted on May 25, 2016May 27, 2016 by Dexlab

View our infographic on the list of most in-demand courses among data enthusiasts who want to advance their careers with the top trends in the job market. Come to DexLab Analytics and launch your career in light speed with the requisite skills to harness the power of data.

Our Courses: MS Excel, Data Science, Business Analytics

A Few Key Business Analytics Tricks Every Manager Must Know

Posted on May 20, 2016October 30, 2017 by Dexlab

The main objective behind using any analytics tool is to analyze data and gather commercially relevant and actionable insights to accelerate results and performances of any organization. But currently there are a variety of tools available so, it often becomes difficult for managers to know which ones to use and when. You may be considering an online certificate in business analytics so reviewing and understanding these key tools may be of great value.

So, we thought you may want to know a few of the key analytics tools in use today and how they can be helpful for different business organizations.

Continue reading “A Few Key Business Analytics Tricks Every Manager Must Know”

Let us Revise Regression Analysis

Posted on May 10, 2016August 13, 2018 by Dexlab

By now every business owner and manager is aware of the latest megatrend related to data analysis and knows that they should make data-driven decisions only at work. Gut feeling and winging it are now practices outdates as they have proved time and again that they fail. But the problem still remains in the know-how of parsing through all the layers of data streaming into your systems. Do you have the requisite know how?

Luckily for you, you may not be the one to crunch all the numbers (phew!). You pay other robotic data analytics personnel to do that for you. But you must correctly understand the analysis report that is handed over to you for interpretation after your colleagues are done with all the heavy lifting. A common practice is the realm of data analysis is regression analysis. Continue reading “Let us Revise Regression Analysis”

Elementary Character Functions in SAS

Posted on December 18, 2015October 5, 2017 by Dexlab

Basically the number of functions present in the SAS program amount to three. They are Character Functions, Numeric Functions and Date and Time Functions. In this post we are going to take a brief look at Character functions of a basic nature.

Character Functions

Suppose that there is this program with the following lines of command:

Data Len_func ; input name $ ; cards; Sandeep Baljeet
Neeta
.
;
run;
data Len_func; set Len_func ; Len=length(name);
Len_N=lengthn(name); Len_C=lengthc(name); run;
proc print; run;

Here,

The function called LENGTH returns the character value’s length.
The function LENGTHN is more or less identical to the LENGTH function. The sole difference between the two lies in the fact that for a value missing character it returns the length that equals to 0 whereas LENGTH returns a value of 1.
The function LENGTHC returns to the program the storage length of particular strings.

The ABC of Summary Statistics and T Tests in SAS – @Dexlabanalytics.

Again let us consider the following lines of code:

Data case ; input name $ ;cards;
sandeep baljeet neeta
;
New_U=upcase(name); New_P=propcase(name); 
run;
proc print; run;

Data Preparation using SAS – @Dexlabanalytics.

Here the following functions are introduced:

The function UPCASE converts all of the letters to the uppercase.
The function PROPCASE serves to capitalize the first letter of all words and converts the remaining to lowercase.
As might be guess from the convention conformed to while naming the function, LOWCASE transforms all letters to their lowercase counterparts.

In the following program commands:

Data AMOUNTS; input NAME $20.; cards;
RAD-HIKA SHARMA RAJARAM PAND-IT SURESH
AA-RT-I
;
RUN;
Data AMOUNTS;
Set AMOUNTS; NAME1=COMPRESS(NAME,'-'); NAME2=COMPBL(NAME);
RUN;
PROC PRINT;
RUN;

Here’s why SAS Analytics Is a Must-Have IT Skill to Possess – @Dexlabanalytics.

Here we can see the following syntax:

Compress (Variable, ”want to remove”);
Compbl (Variable)

The function COMPRESS removes blanks by default. It can also remove a particular specified character value as indicated by the code. In the example cited the character value ‘-‘is compressed.
On the other hand the COMPBL function serves to result in a single blank from multiple ones.

For expert guidance, you will be well advised to enroll yourself in a SAS course from a reputed SAS Training institute. You may consider DexLab Analytics if you are in the vicinity of Delhi or noida.

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Twelve Great Free R Programming E-books

Posted on October 18, 2015October 4, 2017 by Dexlab

To Big Data enthusiasts R is word or rather a letter that needs no introduction. R programming is a programming language that brings the complex world of statistics and datasets at your fingertips. It is mainly used for computing statistics and relevant graphics. The following twelve e-books are not only useful to bring you up to the task for R programming but best of all they are free.

Learning Statistics with R
Author: Daniel Navarro

If you are looking for a guide that will take you through the intricacies of developing software with R be it the basic types and structures of data to more complex topics like recursion, closures as well as anonymous functions. Knowledge of statistics, although helpful, is not an essential pre-requisite .

Continue reading “Twelve Great Free R Programming E-books”

Top 10 Best Hadoop EBooks That You Should Start Reading Now

Posted on October 12, 2015May 23, 2020 by Dexlab

Based on Java, Hadoop is a free open source framework for programming where dealings with huge amounts of processed data in a computing environment is said to be distributed. None other than the Apache Software Foundation is sponsoring it. If you are looking for information about Hadoop, you will like to get in-depth information about the framework and its associated functions. To get you up to the mark with the concepts, the eBooks listed below will prove to be of invaluable help.

MapReduce

If you are looking forward to get started with Hadoop, and maximize your knowledge about Hadoop clusters, this book is of right fit. The book is loaded with information on how t o effectively use the framework to scale apps of the tools provided by Hadoop. This ebook lets you get acquainted with the intricacies of Hadoop with instructions provided on a step-by-step basis and guides you from being a Hadoop newbie to efficiently run and tackle complex Hadoop apps across a large number of machine clusters.

Also read: Big Data Analytics and its Impact on Manufacturing Sector

Programming Pig

If you are looking for a reference from which you may learn more about Apache Pig, which happens to be the engine powering executions of parallel flows of data on the Hadoop framework which also is open source, the Programming Pig is meant for you. Not only does it serve the interests of new users but also provides advanced users coverage on the most important functions like the “Pig Latin” scripting language, the “Grunt” shell and the functions defined by users for extending Pig even further. After reading this book, analyzing terabytes of data is a far less tedious task.

Also read: What Sets Apart Data Science from Big Data and Data Analytics

Professional Hadoop Solutions

This book covers a gamut of topics such as that how to store data with Hbase and HDFS, processing the data with the help of MapReduce and data processing automation with Oozie. Not limiting to that the book further covers the security features of Hadoop, how it goes along with Amazon Web Services, the best related practices and how to automate in real time the Hadoop processes. It provides code examples in XML and Java and refers to them in-depth along with what has been added to the Hadoop ecosystem of late. The eBook positions itself as comprehensive resource with API coverage and exposition of the deeper intricacies, which allow developers and architects to better customize and leverage them.

Apache Sqoop cookbook

This guide allows the user to use Sqoop from Apache with emphasis on application of parameters that are enabled by the Command Line Interface when dealing with cases that are used commonly. The authors offer Oracle, MySQL as well as PostgreSQL examples of databases on GitHub that lend themselves to be easily adapted for Netezza, SQL Server, Teradata etc relational systems.

Also read: Why Getting a Big Data Certification Will Benefit Your Small Business

Hadoop MapReduce Cookbook

The preface of the book claims that the book enables readers to know how to process complex and large datasets. The book starts simple but still gives detailed knowledge about Hadoop. Further, the book claims to be a simple guide on getting things done in one place. It consists of 90 recipes that are offered simply and in a straightforward manner, coupled with systematic instructions and examples from the real world.

Also read: How to Code Colour Values Within SAS Enterprise Guide

Hadoop: The Definitive Guide, 2nd Ed

If you want to know how to maintain and build distributed systems that are both scalable and reliable within the framework of Hadoop then this book is for you. It is intended for – programmers who want to analyze datasets, irrespective of size; and – administrators, who seek to know the setting up and running of Hadoop Clusters, alike. New features like Sqoop, Hive as well as Avro are dealt with in the new second edition. Case studies are also included that may help you out with specific problems.

Also read: How to Use PUT and %PUT Statements in SAS: 6 Tips

MapReduce Design Pattern

If one is to go by the book’s preface, the book is a blend of familiarity and uniqueness. The book is dedicated to design patterns by which we refer to the general guides or templates for solving problems. It is however more open-ended in nature than a “cookbook” as problems are not specified. You have to delve more in the subject matter than mere copying and pasting, but a pattern will get you covered about 90% of the whole way regardless of the challenge at hand.

Also read: SAS Still Dominates the Market After Decades of its Inception

Hadoop Operations

This book is necessary for those who seek to maintain complex and large clusters of Hadoop. Map Reduce, HDFS, Hadoop Cluster Planning. Hadoop Installation as well as Configuration, Authorization and authentication, Identity, Maintenance of clusters and management of resources are all dealt in it.

Programming Hive

Knowledge on programming in Hive provides an SQL dialect in order to query data, which is stored in HDFS, which makes it an indispensable tool at the hands of Hadoop experts. It also works to integrate with other file systems, which may be associated with Hadoop. Examples of such file systems may be MapR-FS and the S3 from Amazon as well as Cassandra and HBase.

Hadoop Real World Solutions CookBook

The preface of this eBook illustrates its use. It lets developers get acquainted and become proficient at problem solving in the Hadoop space. The reader will also get acquainted with varied tools related to Hadoop and the best practices to be followed while implementing them. The tools included in this cookbook are inclusive of Pig, Hive, MapReduce, Giraph, Mahout, Accumulo, HDFS, Ganglia and Redis. This book intends to teach readers what they need to know to apply Hadoop knowledge to solve their own set of problems.

So, happy reading!

DexLab Analytics Presents #BigDataIngestion

Besides, feeding knowledge through eBooks, it is vital to be enrolled for an excellent Big data hadoop certification in Gurgaon. DexLab Analytics is here for you; it offers a gamut of high-end big data hadoop training in Delhi, courses that will surely hone your data skills.

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Data Preparation using SAS

Posted on August 31, 2015July 31, 2018 by Dexlab

Before doing any data analysis, there are tasks which are critical to the success of the data analysis project. That critical task is known as data preparation. You may have heard that in the last years the data production is expanding at an astonishing pace. Experts now point to a 4300% increase in annual data generation by 2020. This can be due to the switch from analog to digital technologies and the rapid increase in data generation by individuals and corporations alike. The most of the data generated in the last few years are unstructured.

In the above context, it is highly important to prepare your data from the unstructured dataset to a structured dataset to do a meaningful analysis.

“Data preparation means manipulation of data into a form suitable for further analysis and processing”

“Data Preparation techniques consists of Cleaning, Integration, Selection and Transformation”

We will discuss some of the data preparation techniques in SAS using SAS. INFORMAT is used to read the data with special characters. FORMAT is used to display the data with special characters.

Data DP.Practice;

length City $10.;
 input City $ ID $ Age Salary DOJ Profit;
 informat Salary dollar6. DOJ ddmmyy10. Profit dollar7.2;
 format Salary dollar6. DOJ ddmmyy10. Profit dollar7.2;
 label DOJ = "Date of Joining";
 rename Salary = Salary_of_Employee;
 datalines;
 Bangalore T101 24 $2,000 12/12/2010 $300.50
 Pune T102 29 $3,000 11/10/2006 $400.50
 Hyderabad T103 $5,000 12/10/2008 $500.70
 Delhi T104 $6,000 12/12/2009 $450.00
 Pune T105 $7,000 12/12/2009 $450.00
 ;
 run;

On the above SAS code, we have used both the INFORMAT and FORMAT to read and display the data with special characters. The SAS INFORMAT statement read the salary as numeric variable and in a specific format i.e. $5,000 which is of 6 characters including $. The FORMAT statement displays the same in your input data. Rename and label statements helps modify the variables metadata for further understanding of the dataset.

We will apply some transformations techniques in a dataset which helps us to apply some advanced analytical techniques in the data. We have a dataset that has various attributes of a customer who has subscribed or not subscribed an edition. In our dataset we have a categorical variable status which holds the observation either “Subscribed” or “Not Subscribed”. We can transform the categorical variable into a dichotomous variable to run a logistic regression on our dataset.

Data media01;
 set DP.media;
 length status $15;
 If status =”subscribed” then status = “0”;
 else status = “1”;
 run;

On the above SAS code, we have applied simple If Else statements to transform our dataset called media. Transforming a categorical variable into a dichotomous variable helps us to apply the analytical techniques that we want to run in our dataset. Once after the transformation is done, the dataset is good to go for the next stage i.e. data analysis.

The more you torture your data i.e. Data Preparation, the more the success on the outcome of the data analysis.

DexLab Analytics offer state of the art SAS training courses. They are a premier SAS training institute that caters to the needs of their students round the clock.

Interested in a career in Data Analyst?
To learn more about Data Analyst with Advanced excel course – Enrol Now.
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Refer to the infographic below to understand the iPhone switching factor:

Character Functions

Suppose that there is this program with the following lines of command:

Again let us consider the following lines of code:

Here the following functions are introduced:

In the following program commands:

Here we can see the following syntax:

Interested in a career in Data Analyst?

Learning Statistics with R Author: Daniel Navarro

MapReduce

Also read: Big Data Analytics and its Impact on Manufacturing Sector

Programming Pig

Also read: What Sets Apart Data Science from Big Data and Data Analytics

Professional Hadoop Solutions

Also read: How To Stop Big Data Projects From Failing?

Apache Sqoop cookbook

Also read: Why Getting a Big Data Certification Will Benefit Your Small Business

Hadoop MapReduce Cookbook

Also read: How to Code Colour Values Within SAS Enterprise Guide

Hadoop: The Definitive Guide, 2nd Ed

Also read: How to Use PUT and %PUT Statements in SAS: 6 Tips

MapReduce Design Pattern

Also read: SAS Still Dominates the Market After Decades of its Inception

Hadoop Operations

Also read: Things to judge in SAS training centres

Programming Hive

Hadoop Real World Solutions CookBook

Interested in a career in Data Analyst?

Interested in a career in Data Analyst?

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Learning Statistics with R
Author: Daniel Navarro