Tag Archives: Big data training in Gurgaon

Streaming Huge Amount of Data with the Best-Ever Algorithm

Can you measure water coming out of a fire hose, while it’s hitting your face? No? Then how would you calculate the amount of data that is constantly being churning out of numerous social media platforms? In simple terms, it’s not feasible, unless you opt for streaming algorithms – these are computer programs that execute such on-the-go calculations.

Streaming Huge Amount of Data with the Best-Ever Algorithm

Data flow is constant and humongous – in order to strategically record the essence, the rest of the data is mostly forgotten. A large pool of data scientists is constantly looking for ways to build a better, improved streaming algorithm, but now I guess their search has come to an end, they have invented something incredible to vouch for. This new, best-of-the-lot streaming algorithm performs miraculously by grasping just what it seems to be necessary, ignoring others. It remembers just that which it has seen the most, and that gives it an upper hand.


Top 4 Best Big Data Jobs to Look For in 2017

Data is now produced at an incredible rate – right from online shopping to browsing through social media platforms to navigating through GPS-enabled smartphones, data is being accessed everywhere. Big Data professionals now fathom the enormous business opportunities by perusing petabytes of data, which was impossible to grasp previously. Organizations are taking the best advantage of this situation and rushing to make the best of these revelations about.


Big data courses are now available in India. DexLab Analytics is the one providing such advanced Big Data Hadoop certification in Gurgaon.


The Future Is In Our Face! How Facial Recognition Will Change Marketing Innovation

Most us are taking a lot of technological marvels around us for granted these days. We have casually taken note of the things like how our smartphones now help us assign photos of people or organize them, or how Facebook usually knows the right people’s faces to tag. However, it has only happened recently, which most people have not realized, that this technology is not so much of a “cool trick” and will actually shape the way people are conducting their business endeavours.

big data facial recognition

These latest technological developments are already being tested out in several different industries and for a lot of different purposes. Like for instance, security scanners at the airports are now making use of this technology to allow the e-passport holders clear their customs faster. And with the further development in facial recognition technology, the border and customs officers will be able to recognize and weed out travellers with fake passports better.


Big Data Analytics and its Impact on Manufacturing Sector

It is no new news that the Big Data and software analytics have had a huge impact on the modern industries. There are several industry disruptors that have surfaced in the past few years and totally changed the lives of all connected humans. Like Google, Tesla and Uber! These are the companies that have used the long list of benefits presented to us by Big Data to expand and infiltrate newer markets, they have helped themselves improve customer relations and enhance their supply chains in multiple segments of market.

Big Data Analytics and its Impact on Manufacturing Sector

As per the latest IDC Research projects the sale of Big Data and analytics services will rise to USD 187 billion in 2019. This will be a huge leap from the USD 122 billion which was recorded in 2015. A major industry that stands to benefit greatly from this expansion which is the manufacturing industry, with the industry revenue projections ranging to USD 39 billion by 2019.


Big Data Analytics Is Helping To Curb Cancer For More Than 40 Years Now

The times now are such that we can name at least one of our friends, relatives or peers who have fought the dreadful battle with cancer. But luckily for us there are several people who along with their loved ones have not only fought this battle with courage but have triumphed to achieve sweet survival. But such glorious accomplishments would not have occurred if it were 40 years ago.

Big Data Analytics Is Helping To Curb Cancer For More Than 40 Years Now


As per the reports, adults who were diagnosed with cancer back in 1975 only had a lowly 50/50 chance of survival after five years of being diagnosed. But today the relative five year after rate of survival across all types of cancer is as close as 70 percent. And for better, the cancer survival rate during the same time frame for child cancer patients within five years of diagnosis has improved from the previously existing 62 percent to 81 percent, which is a steep rise.


Big Data- Down to the Tidbits

Any data difficult to process or store on conventional systems of computational power and storage ability in real time is better known as Big Data. In our times the growth of data to be stored is exponential and so are its sources in terms of numbers.

Big Data has some other distinguishing features which are also popularly known as the six V’s of Big Data and they are in no particular order:

  • Variable: In order o illustrate the variable nature of Big Data we may illustrate the same through an analogy. A single item ordered from a restaurant may taste differently at different times. Variability of Big Data refers to the context as similar text may have different meanings depending on the context. This remains a long-standing challenge for algorithms to figure out and to differentiate between meanings according to context.
  • Volume: The volume of data as it grows exponentially in today’s times presents the biggest hurdle faced by traditional means of systems for processing as well as storage. This growth remains very high and is usually measured in petabytes or thousands of terabytes.
  • Velocity: The data generated in real time by logs, sensors is sensitive towards time and is being generated at high rates. These need to be worked upon in real time so that decisions may be made as and when necessary. In order to illustrate we may cite instances where particular credit card transactions are assessed in real time and decided accordingly. The banking industry is able to better understand consumer patterns and make safer more informed choices on transactions with the help of Big Data.

Big Data & Analytics DexLab Analytics

  • Volatile: Another factor to keep in mind while dealing with Big Data is how long the particular data remains valid and is useful enough to be stored. This is borne out by necessity of data importance. A practical example might be like a bank might feel that particular data is not useful on the credibility of a particular holder of credit cards. It is imperative that business is not lost while trying to avoid poor business propositions.
  • Variety: The variety of data makes reference to the varied sources of data and whether it is structured or not. Data might come from a variety of formats such as Videos, Images, XML files or Logs. It is difficult to analyze as well as store unstructured data in traditional systems of computing.

Most of the major organizations that are found in the various parts of the world are now on the lookout to manage, store and process their Big Data in more economical and feasible platforms so that effective analysis and decision-making may be made.

Big Data Hadoop from Apache is the current market leader and allows for a smooth transition. However with the rise of Big Data, there has been a marked increase in the demand for trained professionals in this area who have the ability to develop applications on Big Data Hadoop or create new data architectures. The distributed model of storage and processing as pursued by Hadoop gives it a greater advantage over conventional database management systems.



One fine day people realized that it is raining gems and diamonds from the sky and they start looking for a huge container to collect and store it all, but even the biggest physical container is not enough since it is raining everywhere and every time, no one can have all of it alone, so they decide to just collect it in their regular containers and then share and use it.

Since the last few years, and more with the introduction of hand-held devices, valuable data is being generated all around us. Right from health care companies, weather information of the entire world, data from GPS, telecommunication, stock exchange, financial data, data from the satellites, aircrafts to the social networking sites which are a rage these days we are almost generating 1.35 million GB of data every minute. This huge amount of valuable, variety data being generated at a very high speed is termed as “Big Data”.



This data is of interest to many companies, as it provides statistical advantage in predicting the sales, health epidemic predictions, climatic changes, economic forecasts etc. With the help of Big Data, the health care providers, are able to detect an outbreak of flu, just by number of people in the geography writing on the social media sites “not feeling well.. down with cold !”.

Big data was used to locate the missing Malaysian flight “MH370″. It was Big Data that helped analyze the million responses and the impact of the very famous TV show “Satyamev Jayate”. Big data techniques are being used in neonatal units, to analyze and record the breathing pattern and heartbeats of babies to predict infections even before the symptoms appear.

As they say, when you have a really big hammer, everything becomes a nail. There is not a single field where big data does not give you the edge, however processing of this massive amount of data is a challenge and hence the need of a framework that could store and process data in a distributed manner (the shared regular containers).

Apache Hadoop is an open source framework, developed by Doug Cutting and Mike Cafarella in 2005, written in java for distributed processing and storage of very large data sets on clusters of normal commodity hardware.

It uses data replication for reliability, high speed indexing for faster retrieval of data and is centrally managed by a search server for locating data. Hadoop has HDFS (Hadoop Distributed File System) for the storage of data and MapReduce for parallel processing of this distributed data. To top it all, it is cost effective since it uses commodity hardware only, and is scalable to the extent you require. Hadoop framework is in huge demand by all big companies. It is the handle for the Big hammer!!