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Attributes of Effective Data Monetization Strategy

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Attributes of Effective Data Monetization Strategy

The saying goes – ‘necessity is the mother of all inventions’ and with the advent of globalization we have witnessed this aphorism in its sincerest form. A new wave of competition and profit generation owing to the advent of the internet, within the labyrinth of our society has led to the creation of Data at a scale previously unthinkable. To capture the essence of this huge amount of data, a new term Big Data, was coined which meant extremely large data sets, which are to be analyzed to reveal patterns that lie within.

Today, technology has become the backbone of the society and data is its vertebrae. The technological boom began and became common around year 2000; this is when data monetization became apparent.

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To simplify, data monetization is the act of generating revenue by exchanging, processing and analysis of data. Processing and analyzing means extraction of value from a particular set of data; eventually this value is to be interpreted to make decisions.

The need for data analysis is apparent since the digital universe is expected to grow 50-fold in terms of data by 2020, yet today only about 1% of the data is analyzed.

To capitalize on data monetization, we can employ the following approaches:

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  • An improvement in internal business processes – To locate synergy between different results, one result may provide some information, but coupled with another piece of result obtained, the synergistic outcome may be far more valuable.
  • Wrapping information around core products and services – This can be accomplished through understanding the target customer (analysis of their online presence can yield valuable information), and many companies are already indulging in these practices.
  • Trade of information to existing markets – This can often lead to be the most profitable of the three approaches, depending on the information, which it possesses.
  • Developing a technological structure – A technological infrastructure, capable enough to churn a real time data and provide real time results would be a boon to any business.


Already 70% of the large institutions purchase external data and monetization of the information asset is still in its infant stage. According to a study performed by Gartner, Data Monetization will be performed by 30% of the companies or more and in a survey conducted by IBM, data monetization was found to be among top 5 priorities of an organization.

The above clearly implies the upward trajectory growth in the near future in this industry, and with the application of the above-mentioned approaches, an effective strategy can be implemented by any organization hoping to be a part of the Data Monetization phenomenon.

Get the best Big data certification with our specialists at DexLab Analytics.

 

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Top Databases of 2017 to Watch Out For

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Data processing is the most talked about topic of this year. From the figure below, you can comprehend that NoSQL and SQL databases are the ones most preferred by the respondents. 

 
Top Databases of 2017to Watch Out For
 

By putting together the percentage of respondents who found them fetching and who called them ‘extremely engaging’, we can conclude who the runner-up is. Here, NoSQL databases secure the second rank with 74.8%.

Continue reading “Top Databases of 2017 to Watch Out For”

How-Stat: This IPL Season Embrace Big Data Analysis and Predict It Right

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How-Stat: This IPL Season Embrace Big Data Analysis and Predict It Right
 

Quick coffee breaks, some time-off from work and engrossing IPL discussions – a perfect office scene described during an IPL season.

 

IPL is here! Indian Premier League 2017 has started!

 
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Cricket is not a sport, but a religion. In India. If there is a match going on, every trivial thing takes a back seat. After all, everything other thing can wait, but not cricket!

Continue reading “How-Stat: This IPL Season Embrace Big Data Analysis and Predict It Right”

Sherlock Holmes Has Always Been a Data Analyst. Here’s Why

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The job of a data analyst or scientist revolves around gathering a bunch of disorganized data, and then using them to build a case through deduction and logic. Finally, following that you will reach a conclusion after analysis.

Sherlock Holmes Has Always Been a Data Analyst. Here's Why

Below quote from Sherlock Holmes is relevant –

“When you have eliminated the impossible whatever remains, no matter how Improbable it is must be the truth.”​

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He always started each case by focusing on the problem.

The problem would sometimes arrive in the form of a letter, sometimes as an item in the newspaper, but most often, it would announce itself by a knock at the door. The client would then present the mystery to Holmes and he would probe the client for salient information. Holmes never relied on guesswork or on assumptions. For Holmes, each new case was unique, and what mattered were reliable and verifiable facts about the case. These gave the investigation an initial focus and direction.

Deduction, Reasoning & Analytics

“It is a capital mistake to theorize before one has data. Insensibly one begins to twist facts to suit theories, instead of theories to suit facts.”

Similarly a data analyst is expected not to assume or formulate theories, which can make the reasoning biased. In his stories, Sherlock Holmes demonstrates his keen powers of observation and deduction from data in front of him. He can decipher how the light enters in Watson’s bathroom based on how his beard is shaved; he attests one person has lived in China from one of his tattoos; he discovers previous financial situation of a man who he had never seen before just looking to the hat the man had just used.

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A data scientist has powerful computational and statistics tools that help him finding patterns amid so much data.

 

In the end, a data analyst’s introduction can be similar to what Sherlock said:

“My name is Sherlock Holmes. It is my business to know what other people do not

know.”

–Team Cosmos

You can learn more about Data analysis by taking up Data analyst certification courses. DexLab Analytics also offers Business analyst training courses.

 

Interested in a career in Data Analyst?

To learn more about Machine Learning Using Python and Spark – click here.
To learn more about Data Analyst with Advanced excel course – click here.
To learn more about Data Analyst with SAS Course – click here.
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To learn more about Big Data Course – click here.

ETL and ETL Testing: The Concepts Explained

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In this New Age, businesses pay maximum attention in collecting customer and transactional data. Businesses with draconian financial reporting and persistent audit requirements look up to ETL, as it offer an organized and integrated solution instead of relying on other apparent solutions like Hadoop.

 

 

ETL and ETL Testing: A Detailed Evaluation

 From Visually.

Continue reading “ETL and ETL Testing: The Concepts Explained”

How will IoT help Industrial Class?

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How will IoT help Industrial Class?

Internet of Things (IoT) is the new buzz these days. The new tide of connectivity goes beyond smartphones and laptops. It includes smart homes, smart cities, smart cars, connected wearables and tries to provide a “Connected Life”. People are increasingly becoming aware of the applications of IoT in their daily lives.

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However, little do they know about the application of IoT in Industries, commonly known as “Industrial IoT”. Through this blog, we would like to share our thoughts on how IoT can save time, energy and money in industries.

SUPPLY CHAIN MANAGEMENT

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Notable research firm, Gartner in its research highlighted that a thirty-fold increase in Internet-connected physical devices by the year 2020 will significantly alter the mechanism in which supply chain operates. For quite some time, ERP and Supply Chain Management have been going hand-in-hand. However, IoT will revolutionize the entire supply chain management process by smartly connecting people, processes, data and things through sensors and devices.

Through IoT, a firm can do the following tasks:

  • Real time fleet management – A firm can optimize its fleet routes by monitoring real time traffic conditions and save fuel costs.
  • Inventory Monitoring– A smart label can be attached to every product/ container so that the movement of every product/ container can be tracked. This will help in reducing the probability of stock out situations due to insufficient stock, theft, pilferage etc. 
  • Storage Condition Control– Temperature stability can be ensured with connected devices and sensors.
  • Predictive Maintenance– IoT can help in knowing about product issues in time to find solutions.

ENERGY MANAGEMENT

Nowadays, every firm is trying to reduce its ecological footprint. IoT can be helpful in achieving this goal through smart energy. A bulb or tube light in the factory can switch on automatically as soon as a worker passes by and switch off once the worker has left. This will help in saving electricity costs.

TIME MANAGEMENT

IoT can be helpful in reducing the overall time taken in production of goods and services. For example- Setup time can be reduced by switching on the machines before the workers arrive at the factory, thanks to connected machines and smart phones. Inventory monitoring and tracking time can also be reduced through IoT. IoT can also be useful in managing the workflow in an event of accident at the factory. In case of an accident, an alarm can be rung in the factory, providing all the relevant details about the accident to the workers. The work can then by diverted through some other route, or some other worker can be employed as soon as possible in place of the injured worker. All this will save time.

Another use can be spending less time on searching for equipments at the workplace. Since equipments and devices are interconnected and geographically tagged, workers can find equipments more easily instead of searching them around. Also, if workers know a piece of equipment has location-tracking, it acts as a deterrent from potential theft (the National Retail Federation estimated that in 2011, employee theft cost companies a whopping $34.5 billion).

Thus, IoT offers great opportunities for the industries, which ensures better and faster production of goods and management of processes. 

To learn more about IoT, take up courses on Machine Learning Using Python. Check out DexLab Analytics for further details on SAS training courses.



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How to Create Repeat Loop in R Programming

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In this tutorial, we will learn to make a repeat loop with the use of R programming.

How to Create Repeat Loop in R Programming

A repeat loop is used to iterate over a block of code over several number of times.

In case of a repeat loop, there is no condition to check in for exiting repeat loop.

Hence, we must ourselves put a condition explicitly within a repeat loop body and make use of the break statement to exit the loop. Failing to do so will result into an infinite loop.

 Syntax of repeat loop

repeat {
   statement
}

When in the statement block, we must use the statement ‘break’ to exit the loop.

 r-repeat-loop-flowchart-120

Example: repeat loop

x <- 1

repeat {
   print(x)
   x = x+1
   if (x == 6){
       break
   }
}

 Output

[1] 1
[1] 2
[1] 3
[1] 4
[1] 5

Note that in the example above, we have only made use of a condition to check and exit the loop when x equals the value of 6.

That is why we see in our output that only values from 1 to 5 get printed.

Why not pull the strings of your career by enrolling for an intensive R programming certification course in Delhi!  DexLab Analytics, being a premier R programming training institute can help you on your endeavour.


This post originally appeared on – www.datamentor.io/r-programming/repeat-loop

Interested in a career in Data Analyst?

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Go Harder, Longer, Faster, And Stronger With Impressive Corporate Training Programs

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Let’s acknowledge, we are living in a digital world. Whether you attend a business dinner, work in the oil fields or inspect warehouse records, the claws of digital technology grips you daily. Today’s digital world revolves around communications, and Avaya is a pioneer in delivering brilliant communications experiences.

 
Go Harder, Longer, Faster, And Stronger With Impressive Corporate Training Programs
 

The expert consultants at DexLab Analytics – a top-notch big data training institute in India is conducting a three-month long training program for selected officials of Avaya at the company’s Pune branch. The consummate team of Business Intelligence, Data Warehousing and Analytics representatives from Avaya will stay in Pune, till the session is completed.

 


 

Headquartered in Delhi, DexLab Analytics feels extremely honoured in heading such an inspiring event with an acute vision of imparting knowledge and skills to individuals. The diligent team of consultants is going to share deeper insights on subjects, like R Programming, Data Science using R, Statistical Modeling using R, Advance Microsoft Excel – VBA, Macros, Dashboards and Tableau BI & Visualization. The sole purpose of this training is to equip the team of Avaya with modern state-of-the-art data technology so as to give them a certain edge over their rival tailing companies.  

 

In this age of digitisation, and when Modijee is in his endeavour to make India Digital India, how can we ignore the reverberating importance of analytical skills! One of the prime advantages of great analytical skills is that you can take crucial decisions to fulfil your organization’s aims and objectives. The vast amount of real time data is at your disposal, and with them, you can easily achieve success and growth in the future.  Therefore, it is evident that the need for analytical skills is going to swell in the coming years, and DexLab Analytics is a reputable business-analytics training institute, which strongly believes in the growing significance of digitisation using data science and analytics.

 


 

In the context of the above discussion, the spokesperson from DexLab Analytics has this to say –


 

“DexLab Analytics with its team of seasoned corporate trainers offering valuable insights about the high-in-demand skills, like Big Data Hadoop, Business Analytics, R Programming, Machine Learning, SAS Programming, Data Science, Visualization using Tableau and Excel are seeking ways to fabricate a path towards corporate training excellence in the wide-encompassing field of Big Data and Data Analytics. Our intensive training module will help officials confer an exhaustive analysis of a newer domain of data science, which will make them more data-efficient and data-friendly.”

 

Recently, the expertise in big data has been recognised as a major component for achieving success in the advanced digital world and the concerned representatives are acknowledging this impressive view. So, let’s hope this take on data analytics motivates more people, paving new roads for data-centric ideas and modules in the near future.

 

Are you looking for intensive SAS courses in Pune? Visit DexLab Analytics and scan through a list of encompassing SAS training courses in Pune.

 

Interested in a career in Data Analyst?

To learn more about Machine Learning Using Python and Spark – click here.
To learn more about Data Analyst with Advanced excel course – click here.
To learn more about Data Analyst with SAS Course – click here.
To learn more about Data Analyst with R Course – click here.
To learn more about Big Data Course – click here.

Battle the Blank Tableau Canvas Blues with These Nifty Tips

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Battle the Blank Tableau Canvas Blues with These Nifty Tips

Do you experience vizzer’s block? Do you feel paralyzed by choices? Do you stare at the blank Tableau canvas, wondering from where to start your viz?

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Though brimming with stories to tell, you are stuck at the get-go. Fortunately, here are a few tricks to help you get over the blank-canvas woes and get yourself rolling.

Draw your mind out

Doodling does help! Draw, doodle or sketch, just kick-start your cognitive thinking abilities. The scribbles don’t need to be pretty or legible, but they have to spur the creative process. So, grab a paper and pen, and start brainstorming.

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And, you don’t have to go it alone. From academic researchers and lifestyle bloggers to professional visual consultants, the entire world is drawing.

Get inspired by ace visualizers

People inspire you, or they drain you – pick them wisely. Keep the right people by your side, they will lift you up and get the better out of you. Be in association with hotshot vizzes, follow maven data journalists and data vizzers, jot down notes and read data-viz pdfs.

ALWAYS, keep your eyes open to stumble across fetching viz, whose idea might work out well for you!

For example, this visualization by Washington Post tells a gripping food-survey story.

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Develop a formidable structure to understand the data better

Frazzled about starting your viz? If affirmative, then this checklist can save your day. It is segregated into two parts – data preparation and data exploration.

Taking the first one first, i.e. Data Preparation:

As boring as it sounds, physical inspection of your data sometimes helps you comprehend the data set’s possibilities and challenges. To draw a clearer picture, here are few things to look into a data set:

 

  • The kind of data in each field
  • The pattern of data structure and format
  • Fields covered and not covered by the data set
  • Highest and lowest values in each field
  • Are there fields that contain null values

 

If you follow the above example, you will find there are multiple levels of data infused in the food-survey data set – where some food items boasts of four sub-categories, while others has only two. Situations like this make it hard to establish a comparison between two food items unless you know that they are at their minimum sub-category.

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Coming to the second one, Data Analysis:

Analyse a data set just like interviewing it. Whenever you feel like going blank by staring at a Tableau canvas, start grilling yourself about data. Do it in a traditional interview way and you are sorted.
 

  • What, how, who, why, when, and where – Evaluate each field and ponder how to apply these questions on each field.
  • Let your inner child smile, while you ask “Why? Why? Why?” to your data.

 

To pop colours on your blank-canvas, interviewing is indispensable.

Remember: Every end is a new beginning

What if my final viz fails to shed light upon the deepest cognizance? Or, how will I feel if my viz cannot do justice to my story. Don’t worry, pondering is common. Get up and hit the road. There are countless number of ways to address a viz and remember that once you finish a viz, it doesn’t mean an end. Remaking and telling stories in newer and innovative ways are something you can always look up to anytime.

5

Turn the volume up and focus

Crank up the music, boost productivity and tune out distractions! Music helps in focusing on work, by diminishing outside noise (phone buzzing, colleagues chatting, TV blasting). Irrespective of the kind of tunes you like, plug in your headphones and say goodbye to the world!

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Recently, tableau bi training courses are gaining a lot of attention. If you are seeking comprehensive tableau certification delhi, scroll through DexLab Analytics.

 

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