Category Archives: Big data training

Big Data is Omnipresent, so Start Praying Paying

Big-Data

Even if you are not a data scientist yet, but there is still data surrounding you and engulfing you in a cloud of structured, specified and targeted data. Data that you use every day on a regular basis and data that actually shapes up your daily routines of commute to work, gym or entertainment. It is like the omnipresent atmosphere that we often take for granted. Why do we say that?

Here is an extract from the life of a non-technical executive of our team, after reading this many of you may feel that this somewhat similar to your story as well.

On an ordinary day, our aforesaid employee gets up in the morning at the ring of his alarm and remembers that his flight will leave at 5 o’ clock that morning. Then he looks at his smart phone and checks the updates on his flight. The flight is on time and the security checks are moving unperturbed. Then he swipes around some more on his smart phone to see if the traffic situation is on his side on this day. He soon finds the traffic is light unlike most other days and decides to cut his commute time very tight expecting himself to reach the airport within 15 minutes. So, he concludes there is ample time for him to leave for the airport at 4:00 am and feeling a sense of confidence about his decision as he made an informed choice so, the chances of things going wrong are low.

Then after his daily ablutions he prepares to set out and opens his Ola/Uber app on phone to call a cab. The app immediately responds with the information that the driver is 2 minutes away. Almost instantaneously the cabbie calls him to understand the precise location of his house and concurs that he will be couple of minutes to get there.

Soon after boarding the cab, our friend opens his health app and connects it via Bluetooth to his smart watch. He notes with a scorn that he is not getting enough exercise and that he only slept 5 hours of deep sleep last night. Then while sitting around being bored in the cab he opens the new Microsoft app that uses your phone camera to look at the picture and guess the age of the face. With further disappointment and in an uncomplimentary way the app gives him a number that is 7 years more than his actual age! But still our executive friend here feels happy as this is a good start of a day. Firstly, because he had the power of data to make educated decisions about some very simple yet troublesome things and two because he got a cab fairly fast.

Now this story may seem like a pretentious rant of pseudo-first world problems, but our point is completely different than the luxurious facilities available to modern urban smart phone owning working class. Our point is to emphasize how almost unknowingly we have let in data into our lives, the myth (and/or fact) of choice is real and we are using it unknowingly while adding and accessing the omnipresent phenomenon of – Big Data.

Yes, Big Data did not just come to office one day and sat in a cabin labelled as “Big Data at work”.  This is like electricity a utility that changes our life and influences our decision making ability. Still unconvinced? Then we ask you to conduct a simple survey among your friends. Ask around to know how many people you know buy over-expensing, sub-par quality products without going through the ratings or reviews. If you hadn’t realized it yet, this is what you would like to label as “Big Data at work”.

Thus, in closing thoughts Big Data analytics is the fundamental ability that enables capabilities to people which will effect and transform our daily lives forevermore and what we see today is evidently just the tip of the ice-berg.

So, start your Big Data certification in Pune today, with DexLab Analytics.

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Big Data’s Evolution in Business Decision Making

Big Data's Evolution in Business Decision Making

We have all established that Big Data is big and all the noise about Big Data is not just hype but reality. With the increase in technology the data generated on Earth is doubling in every 40 months and huge heaps of data keeps coming in from multiple sources. Let’s look at some data to really understand how Big Data is evolving:

  1. The population of the world is 7 billion, and out of these 7 billion, 5.1 billion people use a smart phone device.
  2. On an average everyday almost 11 billion texts are sent across the globe.
  3. The global number of Google searches everyday is 5 billion

But there is an imbalance as we have been creating data but not consuming it enough for proper use. We generate 25 quintillion bytes of data daily through our regular online activities including online communications, online behaviour, video streaming services and much more.

Studies carried out in 2012 showed that the world generated more than 2 zetabytes of data which is roughly equal to 2 trillion gigabytes. By the year 2020, we will generate 35 trillions of data and to manage this growing amount of data we will need 10 times the servers we use now and at least 50 times more data management systems and 75 times the files to manage it all.

The industry is still not equipped to handle such an explosion of data as 80% of it is unstructured data. It is beyond the scope of traditional statistical analysis tools to handle this amount of data as it is too complicated and unorganized.

The talent pool required to effectively manage Big Data will fall short by at least 100 thousand minds as there are only 500 thousand computer scientists but less than 3000 mathematicians. But to truly utilize the complete potential of Big Data we need more human resource and more tools.

The solution to tackle this even bigger problem of Big Data is Big Data Analytics. It is fresh new way of thinking about the company objectives and the strategies created to achieve them. Big Data analytics is the answer behind where the hidden opportunities lie.

SAS, R programming , Hadoop, Pig, Spark and Hive are a few advanced tools that are currently in use in the data analysis industry. SAS experts are higly in demand in the job market recently as it is slowly emerging to be an increasingly popular tool to handle data analysis problems. To learn more about SAS training institutes follow our latest posts in DexLab Analytics.

For more information please read our blog at http://www.dexlabanalytics.com/blog/the-evolution-of-big-data-in-business-decision-making

 

Installation Guide from DexLab Analytics

Dexlab Analytics presents a handy installation guide to all aspiring data analysts to test their hands on Hadoop ecosystems. It only works in a Linux environment and hence, can be tricky to handle. This step-by-step guide will help you through to get this useful software installed in your computer and to start making sense of all the chaos surrounding data.

The Hottest Job Locations for Data Analysis Personnel are:

The current salary trends of analytics personnel

In India the hottest job locations for a data analyst position according to our pay-scale and job scenario survey are – Gurgaon, Mumbai and Bangalore. For more details on payment packages on offer for various data analysis positions view our infographic with numbers based on industry-based survey.

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For More Info On Data Science

Why R Holds Sway over Excel in Big Data

Though the uses of MS Excel are far varied than that of R Programming when it comes to the world of Big Data, R outperforms Excel by leaps and bounds. Handling data as well as manipulating it, is done far more effectively when the tool of R Programming is used. Watch this presentation if you wish to know the exact reasons that give R Programming a competitive edge.

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MS Excel Makes Data Analysis Simple

After watching this video you would agree that data analysis might not be that hard after all. Your humble spreadsheet program, and we are talking about MS Excel, might be all it takes to complete your rudimentary tasks in data analysis. It also worthwhile to mention here that Excel has advanced capabilities in Big Data Analytics which are primarily meant for power users.

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The Amazing Big Data Figures

Huge amounts of data are being generated daily. However traditional systems of managing
data fall short when it comes to analyze such huge datasets. The answer to this riddle lies in Big Data. According to Data Scientists working for IBM, Big Data may be broken up into four dimensions and this presentation brings forth to you some startling and astonishing figures concerning each.

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New Survey Finds Increasing Big Data Adoption

New-Survey-Finds-Increasing-Big-Data-Adoption-01

NewVantage Partners have over the course of the last four years which has found that Big Data has quickly become the part and parcel of the day to day activities of most of Fortune 1000 companies.

The opinion of the crucial decision makers within organizations was taken into account. Financial led the way in investing in Big Date infrastructure. Also of note is the fact in the field of life sciences too usage of big data is increasing by the day.

Other findings of the survey are:

  • In 2012 just a small group of 5% of firms had in place a system of Big Data analytics which in 2015 rose to 63%.
  • In 2012 only 24% of firms claimed to have expectations to invest $10 million or more in Big Data by the year 2017 which rose to 63% in the year 2015.
  • At present a majority of 54% of companies have in place a Chief Data Officer which rose from 12% in the year 2012.
  • In 2012 only 21% of firms reported that their firms held Big Data to be critically important which rose to 70% in the last year.

During the starting year of the survey the executives of organizations were struggling to come in terms to properly perceive the impact and opportunity that Big Data might potentially hold. But today it has become the standard norm for corporate organizations and the focus is rapidly shifting to results produces and the business capabilities enabled by the same.

There is also a need to develop the appropriate metrics. While indeed the majority of Fortune 1000 companies’ implemented capabilities in Big Data, few have demonstrated the business value derived from the investments over time. Organizations with responsible executives for data who report to a Chief Financial Officer are often more likely to have developed financial measurements that are precise.

Innovation remains a source of much promise in the field of Big Data and innovation opportunities need to be identified. There is a dearth of success stories in innovation in things that are enabled by Big Data. Till now its success has largely been limited to savings on cost of operations or being able to analyze data sets that are larger or more diverse. Innovation in Big Data led applications need to be funded more and its practitioners need to exemplify imagination as well as boldness.

Businesses and the analytics industry needs to prepare for both business and cultural change as a new generations take their place in the workplace who have grown up on tools Like R Programming and Hadoop. There is great need for organizations to realize that Big Data is more about cultural change rather than solely technical change.

Big Data Certification

If you too want a piece of the bigger pie of Big Data as a practitioner, then you should try to train yourself for a promising career through proper Big Data Courses in Delhi as conducted by a leading institute like DexLab Analytics.

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Is Predictive Analytics the Future of Big Data?

Is Predictive Analytics the Future of Big Data?The analysis of big data has for long been the cornerstone that technologists and futurists swore by in the recent past.

Enterprises look forward to this analysis as a source of valuable insights the operations related to their business as well as finding correlations within revenue and the activity conducted in the field of sales and marketing.

Frameworks like Hadoop are not only open source but also make data storage more effective both in terms of analytics tools as well as costs associated with the storage of data.

Situation Set To Change

But the prevailing situation is in for some serious change as large data set analysis undergoes a paradigm shift from what happened or is happening to what will happen. Machine learning, the concept of cloud computing as well as technologies that work in-memory all are contributing to this shift.

This shift is termed predictive analysis and promises to be the next big thing in the exciting world of Big Data. With it, Enterprises shall no more be confined to insights gained through analysis of data and react according to it but will be able make pretty accurate forecast of the state of their business a month, week or hours down the line through an effective combination of historical, third party and real time data.

This in turn will allow prompt action on potential problems like failure of machinery or depletion of stock and also to cash in on euphoric or depressed moods common after sporting events. However the focus should be on action than mere forecasts.

The Impact on CRM

CRM or customer relationship management software is a key area where predictive analytics can prove to be of invaluable help. Here predictive analysis will help marketers and sales people to be aware of the impact that their activity will potentially have and also to be able to provide content and pitches that are more personalized. This option is far better than simply to rely on the historical data about interactions made previously.

Inside Sales is a IT specialist in analytics and machine-learning and is one of the companies that is making use of this concept by not limiting itself to analytics but extending to the sphere of predictive analytics with a service based in the cloud.

Their system takes into account data from CRM platforms like Microsoft Dynamics and Salesforce and then proceeds to analyse the same against sales interactions that are suitably anonymized and are in tune of over 100 billion in number from the breadth of its worldwide customer base.

Why It Is Superior

This results in the predictive analytics that is both more effectively enhanced and expanded. This is due to the fact that the data possessed by the company is compared to an aggregated data mass.

When put into practice a company is able to figure out its performance vis-à-vis global and regional trends in sales in this particular sector and to find out key influences like economic factors, current affairs and maybe even the weather on its sales.

You have to know clients as people if you need to win them and then you’ll make more intelligent choices about their needs and practices.

The Workforce

Big Data training is essential for creating a workforce that can suitably match the demands of Big Data and its associated technologies and processes.

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How to Use Big Data for Advanced Customer Experience

How to Use Big Data for Advanced Customer Experience

With computerized information development anticipated to increment by 4,300% all over the world by 2020 and viable weights rising, organizations should now like never before convene the growing requests of their customers.

This digital upheaval is additionally giving remarkable chances to enhance the general client experience by means of big data analytics, as per a study conducted by Big Data Hadoop certification in Gurgaon. This is the procedure of gathering and deciphering these boundless amounts of information to separate the important, savvy, and helpful information that gives worth to a customer.

The following are 3 tips to utilize Big Data to improve general customer experience.

Actualize proactive bill shock administration

Bill shock is client agony from unforeseen allegations and is normally the consequence of broadband clients’ powerlessness to evaluate their huge information utilization, particularly while roaming. These disappointed clients can adversely affect the correspondence administration supplier’s repute and at last prompt income misfortune. Broadband organizations can stay away from this by giving continuous authorization activities and choices, through content warnings or email, permit free limited skimming, and divert clients to exchange information arrangements to dodge upcoming concerns.

Make more intelligent customized shopping encounters

Opt-in versatile showcasing correspondences of focused items and administrations can then be offered through customized messages particular to every phase of the purchaser cycle – mindfulness, engagement, thought, change and steadfastness. Suppose somebody selects to get promoting messages from a retailer who has an outlet in the neighborhood shopping center. GPS-incorporated tracking recognizes that the client is close to the store and sends the client an instant message alarming them to a unique one-day offer. With the client’s advantage provoked, she heads into the store and buys utilizing the coupon code as a part of the instant message.

Diminish holding up time in the line

A service organization, for instance, can deal with this perpetual agony of getting, as to orchestrate a home repair visit by getting the purchaser’s favored channel of correspondence, affirming the evening before in a mechanized way by means of that favored channel, and illuminating the client that the administration tech will call at 8:00 a.m. to tell the purchaser where he remains in the everyday line. This joys the client and disposes of the expense of up to three inbound telephone calls.

You have to know clients as people if you need to win them and then you’ll make more intelligent choices about their needs and practices.

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