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4 Ways Airlines Industry Can Use Big Data for Better Customer Satisfaction

4Ways Airlines Industry Can Use Big Data for Better Customer Satisfaction

While waiting to board your plane, the last thing you would want to hear is – we regret to inform, your flight has been delayed or worse cancelled, leaving you exasperated at the very hour. Even though your flight takes off on time, while waiting in front of the baggage carousel, you may face some moments of anxiety before your bag arrives on time. Luckily, these distresses are now becoming a thing from the past.

Things are changing, and technology world is evolving drastically. By leveraging Big Data and technology upgrades, aircraft industry has been able to improve their operations and work more smoothly and accurately. In addition, the air travel industry is witnessing several benefits, in terms of revenue and consumer satisfaction.

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Here are the ways in which airlines have been using data to derive maximum operational gains everyday:

Smart Maintenance

Wear and tear is common, even the most advanced airplane models equipped with superior technology require time to time maintenance. Owing to this, travelers may experience delays – as per 2014 survey data, mechanical glitches were the second most reason for the majority of flight cancellations and delays. Maintenance takes its toll on airlines potential as the planes need to be grounded for repairing.

With Big Data, airlines can easily track their planes, predict crucial repairs to be done, and provide advice about which parts need to be bought ahead of time and which to keep in reserve on hand for last minute technical issues.

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Reducing Jet Fuel Use

It is impossible to predict how much fuel is used onboard for any given route, historically. But Big Data analytics and cloud data storage has made the impossible possible – you can now track how much fuel is being consumed by each airplane, while taking all the factors into consideration. This paves the way for airlines to draw predictions about the amount of fuel required for a trip to how many number of passengers can board at once.

Taking the Boarding Decisions

Remember, airlines lose if they fly with empty seats, so it’s in their best interest to get everyone onboard. With the help of real-time data, airlines can now easily decide whether to wait for a passenger or leave on time so as not to harass other passengers who might catch connecting flights. Smart boarding is now the key, gone are the days when decisions used to be based on instincts. It’s time to enhance efficiency and performance.

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Tracking Bags

Travelers who travelled before had to be hopeful about their luggage making it back to them. But now, Big Data revolution and tracking technology has changed a lot of things. Nowadays, airlines ensure its travelers the peace of mind that they will surely receive their luggage as promised.  Delta is the first airline that offered tracking data facility for its passengers, using an app format. Customers can easily monitor their bag, reducing the uncertainty revolving luggage arrival.

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Flight operations, crew operations, marketing and air cargo are some areas in airlines industry that boast of rich opportunities for Big Data solutions implementation. In our modern economy, competition is at its peak. To make your airfare rates cheaper and save big on jet fuel, shaking hands with Big Data technology is imperative.

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Top 10 Nifty Tools to Manage Big Marketing Data for Companies

Big Data is the latest buzz. It has to be effectively analyzed to formulate brilliant marketing and sales strategies. It’s of immense importance, as it includes humongous amount of information accumulated about customers from numerous sources like email marketing schemes and web analytics.

 
Top 10 Nifty Tools to Manage Big Marketing Data for Companies
 

However, due to the vast magnitude of information available, it may get quite difficult for marketers to analyze and evaluate all the data in an efficient way. Fortunately, plenty of tools are available in the market that can manage mammoth marketing data and here are few of them:

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Facebook Shut Down AI amid Fears of Losing Control

Facebook Shut Down AI amid Fears of Losing Control
 

Analysts at Facebook promptly shut down the Artificial Intelligence system over concerns they might lose control over the system. Recently, Facebook had developed a new Artificial Intelligence program, which could create its own language with the help of code words to make communication easier and effective. The researchers took it offline, when they understood the language used is no longer English.

 

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Though this isn’t the first time that AIs went a step ahead to take a different route instead of the oh-so-regular training in English language to develop their own more productive language, the recent Facebook incident made us wary about Elon Musk’s warnings about AI. “AI is the rare case where I think we need to be proactive in regulation instead of reactive,” Musk, co-founder, CEO and Product Architect at Tesla once stated at the meet of US National Governors Association. “Because I think by the time we are reactive in AI regulation, it’ll be too late,” he further added.

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Tracing Success in the New Age of Data Science

Each year, pronouncements are made. And each year, a particular job field rides high above the tides of fortune.
For 2017, Data Scientist jobs seem to be #1 Best Job in India. Several magazines and research associates have put Data Scientist jobs at #1 position. No wonder, data science jobs are the hottest jobs in today’s market, hopefully in future too.
So, how do you become a good data scientist? Affordable Data Science Training Course in Gurgaon is now available in India that too quite easily. DexLab Analytics is one such institute that offers state-of-the-art data science training facilities for young aspiring candidates.

Get hold of SAS skills

If you are aware of the top data science skills, you must have known that statistical analysis and data mining calls for SAS specialization. SAS plays an important role in all these disciplines. It has been the pioneer and the most reliable software suit, and for a long time enjoying the monopoly position.

However, since the advent of R and Python, the powerful open source competitors, it is true that the growth curve of SAS has been little but hampered. Nevertheless SAS skills still boast of astounding demand all over the world.

SAS training courses help you understand the nuances of data science. Nowadays, these training’s are not too difficult to find, myriad institutes offer online and classroom training for its students on a regular basis. It is no more too difficult to get a grip on the fundamentals of this subject matter.

The number speaks of positivity

It would be like mine 11th commandment – there is a shortage of data science jobs. It is being predicted that there could be a shortage of 200,000 data scientists by 2020, and this is for real. Indian market is an emerging economy, though data science may not be so famous here as it is in the US, yet I am proud to say that the importance of this field is on the rise.

The survey says – the global demand for data scientists grew by more than 50% in between 2014 and 2015, while the searches have increased by 73%.

The skills you require to possess

By analyzing a whole lot of LinkedIn job postings, we have come to a conclusion that there are 5 high-in demand skills that you need to master in order to ace in data analytics – SQL, Hadoop, Python, Java, and R. Apart from these five, you also need to be quite proficient in Data Visualization and statistics, and try to bring out your creative side to the front.

How much difficult is it to choose a data analytics course?

Make sure, you know what you want, very clearly. Prepare yourself well, before getting into any course. Experience matters, but before that you need encompassing training on the subject matter that can only be offered by a pioneering institute of data science. However, before investing money and your time, check properly if the curriculum satisfies your needs. The material needs to be crisp, to the point and in line with the current industry standards.

DexLab Analytics is a top-of-the-line data science training institute in Gurgaon, offering high-in demand courses on analytics. For any assistance, reach us.

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Maps in Tableau: Key to Answer Data Questions

Maps in Tableau: Key to Answer Data Questions

For creating brilliant data visualization, first you need to know which visual chart type would be ideal for the data story you want to tell. In this post, we will explore maps in Tableau, when and where they seem to be appropriate for particular data visualization, and how to make them more productive. If you want to use a map, make sure you know the reason why.

Maps help you attain, authenticate, or communicate spatial patterns with data. With these maps, you should start your presentation with a spatial question. This spatial question ensures that your map will perfectly find you an answer in the best way possible.

 

For example, answer this question using a data map:

Which country in the US suffers from the highest obesity rate?

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How much time did it take to answer that question? Did you quickly find the actual location without fuddling too much over the darker-colored country? I guess not. However, this map might not be the best path to answer this spatial question.

Now, let’s use the bar chart below to answer the same question.

 

It is easier to discover the answer here.

By combining the map and bar chart together, the answer to your spatial question can easily be derived.

 

Basically, maps are great for answering these two types of spatial questions:

  • What is the value for a specific location or mark on the map?
  • How do patterns compare between locations, regions, or attributes?

 

Go through the following tips to answer these questions better.

How to determine the value for a specific location or a mark on map?

Tooltips are the perfect way to move your mouse over a mark and observe a list of all the underlying dimensions and measures present.

You can easily edit a tooltip to include both dynamic and static text.

For example, identify which of these tooltips reveals a story about earthquakes in Japan.

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Also, the Tooltip improves speed-to-insight because the viewers of the map can easily find individual locations they want to find.

For example, find out the internet usage percentage in Uganda.

uganda

How do patterns compare between regions, locations or attributes?

To give answer to this question with a map, you must allow a direct comparison to be established between the data, symbols and even colors.

For example, while establishing a comparison between these two sets of unemployment data, the default color encoding doesn’t add any value for making direct comparisons. The reason being: the dark red doesn’t stand for the same value in both maps.

In turn, this situation can be very confusing for users who have no idea about the details of the data.

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The best way to deal with the problem is by getting an assurance that the color ramps in both maps use the same range.

Also, you can make your date easier for comparison by adjusting the color scheme, so that different color groups exude similar semantic meaning. Semantically-resonant colors help in processing information faster.

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In case, you want to learn more about Tableau, check out our blogs published on DexLab Analytics. We offer state-of-the-art Tableau training courses in Delhi, for any assistance reach out to us.

 

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Televisory Launches Data Analytics & Operational Benchmarking Platform

Televisory Launches Data Analytics & Operational Benchmarking Platform
 

Televisory, a start-up based out of India and Singapore, has launched its data analytics and operational benchmarking platform. The platform can measure real-time operational and financial performance of companies. While the firm has chosen to launch its platform from the US, its services are available globally.

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Artificial Intelligence: Let’s Crack the Myths and Unfold the Future to You

Artificial Intelligence: Let’s Crack the Myths and Unfold the Future to You

A lot of myths are going around about Artificial Intelligence.

In a recent interview, Alibaba founder Jack Ma said AI can pose a massive threat to jobs around the world, along with triggering World War III. The logic of shared by him explained that in 30 years, humans will be working for only 4 hours a day, and 4 days a week.

Fuelling this, Recode founder Kara Swisher vouched for Ma’s prediction. She supported him by saying Ma is “a hundred percent right,” adding that “any job that’s repetitive, that doesn’t include creativity, is finished because it can be digitized” and “it’s not crazy to imagine a society where there’s very little job availability.” 

Besides, I find all these stuffs quite baffling. I think that if AI is going to be the driving force towards innovation and bringing in a new technological revolution, it’s upon US to curate the opportunities that will require new jobs. Apocalyptic predictions just don’t help.

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Let’s highlight the myths and the logical equations:

Myth 1: AI is going to kill our jobs – it can never happen

Remember, it’s humans who have created robots. We excel at mechanizing, systematizing and automating. We spurred the automation drive, while infusing intelligence to the machines.

The present objective is to create AIs that can work together with human intelligence to develop new narratives for problems we are yet to solve. To solve these new problems, we need new kinds of jobs – there’s a great scope of opportunity, let’s not believe that AI will kill our jobs.

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Myth 2: Robots are AINot at all.

From drones to self-organizing shelves in warehouses to machines sent to Mars, all are just machines programmed to function.

Myth 3: Big Data and Analytics are AI. Who said that?

Data mining, Data Science, Pattern Recognition – they are just human-created models. They might be intricate or complicated in nature, but not AI. Data and AI are two entirely different and divergent concepts.

Myth 4: Machine Learning and Deep Learning are AI. Again a big NO.

Though Machine Learning and Deep Learning are a part of the enormous AI tool kit, they are not AI. They are just mere tools to program computers to tackle complex patterns- like the way your email filters out spam by “understanding” what hundreds and thousands of users have identified as spam. They look uber smart, undeniably, in fact scary at times, when a computer wins against a renowned expert at the game GO, but they are definitely not AI.

Myth 5: AI includes Search Engines. Definitely NO.

Search Engines have made our lives easier, undoubtedly. The way you can search information now was impossible few years back, but being the searcher, you too contribute the intelligence. All the computer does is identify patterns from what you search and suggest it to others. From a macro perspective, it doesn’t actually know what it finds because it’s dumb in the end. We feed them intelligence, otherwise they are nothing.  

So, instead of panicking about the uncertainties that AI may bring into our lives, we should take a bow and appreciate the efforts humans gave into creating something so huge, so complex like AI.

And remember, AI has always created jobs in the past and didn’t take them. So, be hopeful!

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INTCK and INTNX: All about SAS Dates and Computing Intervals between Dates

INTCK-and-INTNX

The INTCK and INTNX functions in SAS helps you compute the time between events. This technical blog is based on the timeline of living US presidents, sourced from a Wikipedia table. The table data shows the number of years and days between events.

So, let’s start.

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Gaps between dates

To calculate the interval between two dates, you can use these two SAS functions:

The INTCK function returns the number of time units between dates. The time unit can be selected in years, months, weeks, days, or whatever you feel like.

The INTNX function helps you compute the date that is 308 days away in the future from a specific date. This was just an example to help you understand what it means. The INTNX function returns a SAS date that is particular number of time units away from a particular date.

These two functions share a complimentary bond: where one calculates the difference between two dates, the other entitles you to add time units to a specified date value. Also, the INT part in both the functions denotes INTervals, and the terms INTCK and INTNX means Interval Check and Interval Next, respectively.

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How to calculate anniversary dates

These two prime functions tend to be useful in counting the number of anniversaries between two dates along with calculating a future anniversary date. Use the ‘CONTINUOUS’ option for the INTCK function and the ‘SAME’ option for the INTNX function in the following manner:

The ‘CONTINUOUS’ option in the INTCK function helps you count the number of anniversaries of one date that occur before a second date. For example, the statement

Years = intck('year', '30APR1789'd, '04MAR1797'd, 'continuous');

returns the value 7 because there are 7 full years (anniversaries of 30APR) between those two dates. Without the ‘CONTINUOUS’ option, the function returns 8 as 01JAN occurs 8 times between those dates.

The statement

Anniv = intnx('year', '30APR1789'd, 7, 'same');

returns the 7th anniversary of the date 30APR1789. In some ways, it returns the date value for 30APR1796.

The most exciting part about these two functions is that they automatically handle leap years! Yes, you read that right. If you ask for the number of days within two dates, the INTCK function will show leap days in the result. If an event takes place on a leap day, and you ask the INTNX function to reveal the anniversary date, it will report 28FEB of the next year to the next anniversary date.

An algorithm calculating years and days between events

Go through the following algorithm to calculate the number of years and days between dates in SAS:

  • Use the INTCK function with the ‘CONTINUOUS’ option to calculate the number of completed years between two dates
  • Use the INTNX function to discover a third date, i.e. anniversary date, which is the same month and day like the start date, but takes place less than a year before the end date.
  • Use the INTCK function to ascertain the number of days occurring between the anniversary date and the end date.

Here are the data steps that enable you to compute the time interval in years and days between the first few US presidential inaugurations and deaths.

data YearDays;
format Date prevDate anniv Date9.;
input @1  Date anydtdte12.
      @13 Event $26.;
prevDate = lag(Date);
if _N_=1 then do;                               /* when _N_=1, lag(Date)=. */
   Years=.; Days=.; return;            /* set years & days, go to next obs */
end;
Years = intck('year', prevDate, Date, 'continuous'); /* num complete years */
Anniv = intnx('year', prevDate, Years, 'same');      /* most recent anniv  */
Days = intck('day', anniv, Date);                    /* days since anniv   */
datalines;
Apr 30, 1789 Washington Inaug
Mar 4, 1797  J Adams Inaug
Dec 14, 1799 Washington Death
Mar 4, 1801  Jefferson Inaug
Mar 4, 1809  Madison Inaug
Mar 4, 1817  Monroe Inaug
Mar 4, 1825  JQ Adams Inaug
Jul 4, 1826  Jefferson Death
Jul 4, 1826  J Adams Death
run;
 
proc print data=YearDays;
var Event prevDate Date Anniv Years Days;
run;

 

LivingPresidents3

 

In a nutshell, the INTCK and INTNX functions are consequential for calculating intervals between dates. In this blog, I discussed about two-less-popular options inn SAS, for more such SAS training related blogs, follow us at DexLab Analytics.

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This post originally appeared onblogs.sas.com/content/iml/2017/05/15/intck-intnx-intervals-sas.html
 

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5 New-Age IT Skill Sets to Fetch Bigger Paychecks in 2017

Technology is the king. It is slowly intensifying its presence over workplaces, and is one of the chief reasons why companies are laying off employees. Adoption of cutting-edge technologies is believed to be the main reason of job cuts and by now if professional techies are not properly equipped with newer technologies under their sleeves, the future of human workforce seems bleaker.

 
5 New-Age IT Skill Sets to Fetch Bigger Paychecks in 2017
 

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A recent report says – India would lose about 69,000 jobs until 2021 due to the adoption of IoT, so do you really think human intelligence is losing its intellect? Will AI finally surpass brain power?

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