We will start off this post with a little bit of trivia.
- The advertised median salary on offer for technically inclined professionals with expertise in Big Data, which today is a highly sought-after skill is no less than $124,000 inclusive of compensation and bonuses.
- Cisco, IBM and Oracle together had 26,488 positions that were open during the previous year which required expertise in Big Data.
- EMC or Dell required 25.1% of all positions in Big Data to have analytics tracks.
- Data Warehousing, VMWare and developing programming expertise in Python are the fastest growing skill sets that are in demand by companies that are on an expansion of their development teams in Big Data.
Continue reading “Why the Job Market is Going Gaga over Big Data”
Following a massive explosion in the world of data has made the slow paced statisticians into the most in-demand people in the job market right now. But why are all companies whether big or small out for data analysts and scientists?
Companies are collecting data from all possible sources, through PCs, smart phones, RFID sensors, gaming devices and even automotive sensors. However, just the volume of data is not the main factor that needs to be tackled efficiently, because that is not the only factor that is changing the business environment, but there is the velocity as well as variety of data as well which is increasing at light speed and must be managed with efficacy.
Why data is the new frontier to boost your sales figures?
Earlier the sales personnel were the only people from whom the customers gathered data about the products but today there are various sources from where customers can gather data so people are no longer that heavily reliant on the availability of data.
Continue reading “Infographic: How Big Data Analytics Can Help To Boost Company Sales?”
Hadoop is being increasingly used by companies of diverse scope and size and they are realizing that running Hadoop optimally is a tough call. As a matter of fact it is not humanly possible to respond to the changing conditions in real time as these may take place across several nodes in order to fix dips in performance or those that are causing bottlenecks. This performance degradation is exactly what needsto be critically remedied in cases where Hadoop is deployed on large scales where Hadoop is expected to deliver results critical to your business in the proper time. The following three signs signal the health of your Hadoop cluster.
The Out of Capacity Problem
The true test of your Hadoop infrastructure comes to fore when you are able to efficiently run all of your jobs and complete them within adequate time. In this it is not rare to come across instances where you have seemingly run out of capacity as you are unable to run additional application. However monitoring tools indicate that are not making full use of processing capability or other resources. The primary challenge that now lies before you is to sort out the root cause of the problem you have. Most often you will find them to be related to the YARN architecture that is used by Hadoop.YARN is static in nature and after the scheduling of jobs the process of adjusting system and network resources. The solution lies in configuring YARN to deal with worst case scenarios.
Continue reading “Things To Be Aware Of Regarding Hadoop Clusters”
I hope this post will help you to answer some questions related to Apache spark that might be coming into your mind these days related to Spark in Big Data Analytics.
Continue reading “Will Spark Replace Hadoop?”
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.
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.
More and more data-hungry professionals are seeking excellent Data Science training in Delhi. If you are one of them, kindly drop by DexLab Analytics: we are a pioneering Data Science training institute. Peruse through our course details for better future.
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Since a long time we are providing Big Data Hadoop training in Gurgaon to aspirant seeking a career in this domain.So, here our Hadoop experts are going to share a big data Hadoop case study.Think of the wider perspective, as various sensors produce data. Considering a real store we listed out these sensors- free WiFi access points, customer frequency counters located at the doors, smells, the cashier system, temperature, background music and video capturing etc.
While many of the sensors required hardware and software, a few sensor options are around for the same. Our experts found out that WiFi points provide the most amazing sensor data that do not need any additional software or hardware. Many visitors have Wi- Fi-enabled smart phones. With these Wifi log files, we can easily find out the following-
Continue reading “Using Hadoop Analyse Retail Wifi Log File”
Fresh on the heels of the advent of the new year, Big Data enthusiasts might wonder what the coming year beholds like machine learning updates, data as a service that works in real time, Markets of algorithms, Spark and much, much more.
- The Emergence of the Chief Data Officer
The sweeping changes in recent times has made aware that enterprises realize that they are in real need of a working strategy in order to compete with competitors who are digital-native.This strategy is ideally formed by a Chief Data Officer.
- Empowering Business Users
Due to a lack of proper talent in the Big Data industry more tools will emerge that reveal information to the users directly. Salesforce and Microsoft are both letting non-coders create apps that are intended to make visualizations of business data.
In recent times it is often seen that organizations embed analytic function pieces directly in the required apps. In fact, according to the predictions by the IDC by 2020, it is projected that all software related to business analytics will include prescriptive analytics which will be based on cognitive computing functionality.
- An End to Talent Shortage
There is an acute shortage of data scientists. As reported recently by A.T. Kearney, the business consultancy no less than 72 % of global companies that are the leaders in their respective markets, find it hard to recruit quality talent in data science. But recent predictions by the International Institute for Analytics run contrary. According to it that scarcity of quality talent in the field may be reduced in 2016 as companies put into use new tactics.
- Machine Learning Comes of Age
Machine learning basically revolves around the creation of algorithms that lets computers sort of learn from experience. It is attracting more than its fair bit of attention in organizations that seek to automate processed that otherwise require the intervention of humans.
- The Rise of the Data-As-A- Service Model of Business
The recent acquisition of the Weather Company by IBM shows signs on what is looming over the horizon. In all likelihood companies will adopt the business model of services that consist of data streams and package and sell the data acquired by them.
Big data Hadoop courses are hitting it big in the world of business whether it is healthcare, manufacturing, media or marketing. Data is generated everywhere, and Hadoop is a readily available open source Apache software program that can be utilized to crunch and store Big Data sets.
As per reports from the Transparency Market Research the forecast shows a promising growth opportunity from the existing USD 1.5 million back in 2012 to USD 20.8 million within 2018. These promising growth numbers suggest that there will be an increased need for human resources to manage, develop and oversee all the Hadoop implementations.
DexLab Analytics Presents #BigDataIngestion
Many experts believe that one can learn any new subject by simple self-study if only you invest enough time and sincere predisposition towards a topic. After all self-study is actually what a person does to acquire knowledge about any given topic. Be it how to fix a leaky faucet or learn a new language or learn strum a guitar. Studying is on one’s own in any case. But to be an expert in a given field, you have to study on your own while you also need to invest your energy in the right direction. And to know the right direction, you need a mentor or a guide to lead the way.
But if you want to test the waters, and tinker with Hadoop to understand its basics, you can go through the wide range of documents available at the Apache Hadoop website for your perusal. Also try downloading the Hadoop open source release to get the feel of the program while tinkering with different features.
Here are 5 online sources where you can seek some basic introduction to Hadoop for big data:
- IBM’s open sources, Hadoop Big Data for the Impatient is a good option to go through the basics of Hadoop. It also offers a free download of Hadoop image (you might need Cloudera) to help you work with examples of Hadoop-based problems. You will also be able to get an idea of Hive, Oozie, Pig and Sqoop. The course is available in Vietnamese, Chinese, Spanish and Portuguese.
- Cloudera offers a Cloudera essentials course for Apache Hadoop. Apache Hadoop chapter wise video tutorials are available with Cloudera essentials. But this course is mainly targeted at administrators and those who are well-acquainted with data science, to update their skills on the subject.
- YouTube also offers a long list of videos on Hadoop topics for beginners. Some are good while others may not be so helpful for the Hadoop virgins. Simply type Hadoop and you will find a never-ending list of videos related to Hadoop. Some are quite useful for clarifying simple doubts related to Hadoop.
- Udemy is another site where you can get some free videos as well as a few for a fee. Simply put Hadoop free on the search bar at their homepage and see what comes up.
- Udacity was developed by Silicon Valley giants like FaceBook, Cadence, Twitter and the likes. They offer a 14-day free trial with free course materials. But you will need to pay for the course if you do not finish the course within 14 days.
Seeking a good and reliable Hadoop training in Delhi? When DexLab Analytics is here, why look further! Being a recognized Big Data Hadoop institute in Gurgaon, the courses are truly interesting.
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2015 is nearing its end and Big Data has finally come of age. Business intelligence or BI as it is often referred to is also progressing in leaps and bounds.
Which Business Intelligence Software Will you Buy
Many key trends are all set to emerge in the Business Intelligence market in 2016. Spending on traditional BI platforms has almost come to an unceremonious end.
- As a matter of fact Gartner predicts a decline of more than 20% on traditional processes related to Business Intelligence in the coming year.
- This is in sharp contrast to tools regarding data discovery and self-service Business Intelligence like tableau bi software which witnessed an incredible growth of 77.7% in the last fiscal.
- Seattle is the place to be as both AWS and MSFT Azure bet big in the market for cloud BI. All eyes are now set on Google as we await their counter move making the competition really interesting.
- Cloud BI services will face a hard battle as they compete with AWS QuickSight and cannot compete with the margins of AWS.
- In general it may safely be predicted that the industry related to financial services will adopt the cloud with 20% of top financial institutions announcing a Cloud-first or Cloud-exclusive strategy regarding IT.
- Industry insiders are abuzz and fascinated by the Internet of Things or IoT, but nevertheless it will soon dawn upon people that the data derived from sensors though abundant is for most uses quite useless.
- Due to this there will emerge huge discussion which should be pragmatic in nature regarding how the data streams from sensors may be cleaned and the necessity of merging static data and that emerge from that of IoT.
- Smart Cities are the way of the future and give us a fore-glimpse of how data from traffic sensors, transportation logs, social networks, emergency and census personnel may be used to drive quick insights and response plans for the community as a whole to natural disasters and events related to national security.