Big Data Hadoop Archives - DexLab Analytics | Big Data Hadoop SAS R Analytics Predictive Modeling & Excel VBA

DexLab Analytics is Providing Intensive Demo Sessions in March

Posted on March 14, 2019March 14, 2019 by Dexlab

DexLab Analytics is Providing Intensive Demo Sessions in March

The internet has spurred quite a revolution – in several sectors, including education. Interested candidates are at liberty today to learn a vast array of things and garner a humongous pool of knowledge. Online demo sessions further add to the effect. These demo sessions are state-of-the-art and in sync with the industry demands. They are one of the most effective methods of learning and upgrading skills, particularly for the professionals. They transform the learning process and for all the good reasons.

DexLab Analytics is a premier data science training institute that conducts demo sessions, online and offline regularly. These demo sessions are indeed helpful for the students. With an encompassing curriculum, a team of experts and a flexible timing, the realm of demo sessions has become quite interesting and information-laden.

Talking of online sessions, they are incredibly on-point and high on flexibility. With daring innovations in technology, no longer do you have to travel for hours to reach your tuition center. Instead, from the confines of your home sweet home, you can gain access to these intensive demo sessions and learn yourselves. Adding to that, the medium of learning is easy and user-friendly. The millennial generation is extremely tech-savvy that leaves no room for difficulties learning online.

Moreover, we boast of top-of-the-line faculty strength, well-versed in the art and science of data science and machine learning. With years of experience and expertise, the consultants working with us are extremely professional and knowledgeable in their respected field of study. Lastly, online demo sessions are great tools for career advancement. While working, you can easily upgrade your skills in your own time – boosting career endeavors further. The flexibility of learning is the greatest advantage.

This month, DexLab Analytics is organizing the following demo sessions; kindly take a note of the date and timing:

Demo session on Machine Learning, Deep Learning and Python – Saturday 16th March at 2 PM by industry professionals
Demo session on Data Visualization and Reporting – Saturday 23rd March at 11 AM by industry professionals
Demo session on Credit Risk Modelling – Saturday 16th March at 2 PM by industry professionals

For more information on big data Hadoop training in Delhi, follow DexLab Analytics.

Interested in a career in Data Analyst?
To learn more about Data Analyst with Advanced excel course – Enrol Now.
To learn more about Data Analyst with R Course – Enrol Now.
To learn more about Big Data Course – Enrol Now.
To learn more about Machine Learning Using Python and Spark – Enrol Now.
To learn more about Data Analyst with SAS Course – Enrol Now.
To learn more about Data Analyst with Apache Spark Course – Enrol Now.
To learn more about Data Analyst with Market Risk Analytics and Modelling Course – Enrol Now.

6 Questions Organizations Should Ask About Big Data Architecture

Posted on May 24, 2017October 4, 2018 by Dexlab

Big data come with big promises, but businesses often face tough challenges to determine how to take big advantage of big data and deploy the effective architecture seamlessly into their system.

From descriptive statistics to AI to SAS predictive analytics – every single thing is spurred by big data innovation. At the 2017 Dell EMC World conference, which took place on Monday, the chief systems engineer for data analytics at Dell EMC, Cory Minton – gave a presentation simplifying the biggest decisions an organisation need to make when employing big data.

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

Let’s get started with 6 questions that every organization should ponder over before stepping into the tech space:

Buy or build?

Do you want to buy a successful data system or build one right from the scratch? Minton said, though buying offers simplicity and a shorter time to value, it comes at a hefty price. The building idea is good and provides huge scale and variety, but it is very complicated, and interoperability is one of the biggest issues faced by admins, who take this route.

Teradata, SAS, SAP, and Splunk can be bought, while Hortonworks, Cloudera, Databricks and Apache Flink are used to build big data systems.

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

Batch or streaming data?

Products like Oracle, Hadoop MapReduce and Apache Spark offers batch data – they are descriptive and can manage large chunks of data. On the other hand, Products like Apache Kafka, Splunk, and Flink creates potential predictive models, coupled with immense scale and variety.

Kappa or lambda architecture?

Twitter is the best example of lambda architecture. This kind of architecture works best as it gives the organisation access to batch and streaming insights along with balances lossy streams, as said by Minton. While, kappa architecture is hardware efficient and Minton recommends it for any newbie organisation starting fresh with data analytics.

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

Private or public cloud?

Ask your employees, about what kind of security platform they are comfortable working, and then decide.

Physical or virtual?

Minton said – a decade ago, the debate surrounding virtual or physical infrastructure used to gain more momentum. Now, things have changed. Virtualization has become so competitive that sometimes it outdoes physical hardware. Today, it stresses more on what works for our infrastructure rather than individual preferences.

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

DAS or NAS?

Minton said Direct-attached storage (DAS) is the only way to initiate a Hadoop cluster. Today, the tides are changing; with increasing bandwidth in IP networks, the Network-attached storage (NAS) option is becoming more feasible for big data implementation.

DAS is easily initiated and the model works well within software-defined concepts. NAS is efficient in handling multi-protocol needs, offers functionality at scale and addresses security and compliance issues.

For more big data related news, check out our blog section in DexLab Analytics. We are a pioneering data analyst training institute, offering excellent Big data hadoop certification training in Delhi.

Interested in a career in Data Analyst?
To learn more about Data Analyst with Advanced excel course – Enrol Now.
To learn more about Data Analyst with R Course – Enrol Now.
To learn more about Big Data Course – Enrol Now.
To learn more about Machine Learning Using Python and Spark – Enrol Now.
To learn more about Data Analyst with SAS Course – Enrol Now.
To learn more about Data Analyst with Apache Spark Course – Enrol Now.
To learn more about Data Analyst with Market Risk Analytics and Modelling Course – Enrol Now.

Are You a Student of Statistics? – You must know these 3 things

Posted on April 22, 2016May 23, 2020 by Dexlab

We a premiere statistical and data analysis training institute offering courses on Big Data Hadoop, Business intelligence and Ai. We asked our faculty to tell us the three most important things that every student of elementary statistics should know.

So, let us get on with it:

The notion that statistics is about numbers, is in the context only: statistics involves a rich treasure trove of numeric and graphical representation of displaying data to quantify them also it is very important to be capable of generating graphs along with numbers. But that is not the half part of statistics and the main interesting aspect is related to making the big leap from numbers and graphs to the realistic worldly interpretations. Uncannily statistics also poses to be a fascinating philosophical tension raising the question and healthy skepticism about we believe in and what we do not.
The analysis part is not the most crucial part of a statistical study, the most important part lies with the when, where and how of gathering the data. We must not forget when we enter each number or data, calculate and plot the strategies we build on our understanding, but many a times at the time of interpretation that each every graph, data or number is a product of a fallible machine, be it organic or mechanical. If we are able to take proper care at the stage of sampling and observation we will be able to obtain great dividends at the final stage of interpretation and analysis of all our statistical efforts.
All statistical functions off all kinds of mathematical sciences are based on a two-way communication system. This communication system should be between the statistician and non-statistician end. The main aim of statistical analysis is to put forward important social, public and scientific questions. A good statistician knows how to communicate with the public especially with those who are by and large not statisticians. Also the public here plays an important role and must possess simple idea of statistical conclusions to grasp what the statisticians have to say to them. This is an important criterion to be incorporated in the K-12 and college curriculum for elementary statistical students.

If you agree with our views and would like to discuss further on statistics and its application on data analysis then feel free drop by DexLab Analytics and stay updated on the latest trends in data management and mining.

Interested in a career in Data Analyst?
To learn more about Data Analyst with Advanced excel course – Enrol Now.
To learn more about Data Analyst with R Course – Enrol Now.
To learn more about Big Data Course – Enrol Now.
To learn more about Machine Learning Using Python and Spark – Enrol Now.
To learn more about Data Analyst with SAS Course – Enrol Now.
To learn more about Data Analyst with Apache Spark Course – Enrol Now.
To learn more about Data Analyst with Market Risk Analytics and Modelling Course – Enrol Now.

Infographic: How Big Data Analytics Can Help To Boost Company Sales?

Posted on February 26, 2016July 13, 2018 by Dexlab

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?”

Things To Be Aware Of Regarding Hadoop Clusters

Posted on February 12, 2016May 23, 2020 by Dexlab

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”

Will Spark Replace Hadoop?

Posted on February 3, 2016September 4, 2017 by Dexlab

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?”

How Hadoop makes Optimum Use of Distributed Storage and Parallel Computing

Posted on September 29, 2015September 29, 2015 by Dexlab

Hadoop is java based open source framework by Apache Software Foundation, It works on the principle of distributed storage and parallel computing for large datasets on commodity hardware.

Let’s take few core concepts of Hadoop in detail :

Distributed Storage – Here in Hadoop we deal with files of size TB or may be PB. We divide each file into parts and store them on multiple machines. It replicates each file by default 3 times (you can change replication factor as per your requirement) , 3 copies of each file minimizes the risk of data loss in Hadoop Eco system. In real life as you store a copy of car key at home to avoid problem in case your keys are lost

Parallel Processing – We have progressed a lot in terms of storage space, processing power of processers but seek time of hard disk has not improved significantly to overcome this issue in Hadoop to read a file of 1 TB would take a long time by storing this file on 10 machines on a cluster, we can reduce seek time by upto 10 times.
HDFS has a minimum block size of 64MB to store large files in an optimized manner.

Let me explain you with some calculations:
Traditional System Hadoop System (HDFS)
File Size – 1TB (1000000000 KB) 1TB (1000000000 KB)
Windows Block Size – 8KB 64MB
No. of Blocks = 125000000 (1000000000 /8) 15625 (1000000000 /64000)
Assuming avg seek time = 4ms 4ms
Total Seek Time =125000000* 4 15625 * 4
= 500000000ms =62500ms
As you can see due to HDFS Block size of 64MB we could save 499937500ms (i.e. 99.98%of seek time) while reading 1TB of file in comparison to windows system.

We could further reduce seek time by dividing file into n parts and saving them on n no. of machines then seek time for 1TB file would be 62500/n ms.

Here you can see one use of parallel processing i.e. parallel reading of a file in cluster on multiple machines.
Parallel processing is a concept on which Map Reduce paradigm work in Hadoop, it distributes a job into multiple tasks for processing as a Map Reduce job more details in coming up blog for Map Reduce.

Commodity Hardware – It is the usual hardware that you use as your laptops / desktops in place of High Availability reliable IBM Machines. The use of commodity hardware has helped business hubs to save a lot of infrastructure cost. Commodity hardware is approx. 60% cheaper than High Availability reliable machine.

Call us to know more

Gurgaon

Kolkata