What is Big data and it’s characteristics?

The term Big Data describes the large volume of data (structured or not) that day by day originate from the usual activity of a company. But the really important thing is not how much data we have, but what we are going to do with them. Getting into the world of ” Big Data ” can be key to business, and how to take advantage of all the information that is generated in the day-to-day activity, but if it is not well defined, it will be a time-consuming project and resources, without adding value to the company. If you want to know what Big Data is , I encourage you to read this entry.

Big Data is not just a lot of data

In addition to having a large volume of information , to talk about Big Data we must take into account other “Vs”, in particular the three:

Volume: The data in the society of information grow at an exponential rate. The data of the IoT sensors that measure humidity, position or temperature, social networks, mobile devices… are added to the usual daily operational data , such as commercial transactions   .

Variety: As we have said, the sources of information are many, and each one has a different format. We have data structured databases of data traditional as well as text documents, videos, emails, tweets ….

Speed: One of the most important characteristics of Big Data is the need to give a response “almost” in real time. With the technological advances of recent years has made it possible to manage and process the large volumes of data heterogeneous within a reasonable time. In a Big Data project it is possible to add data sources (such as logs) that were not previously used because technologically it was not possible to process them in real time.

When talking about speed it is necessary to take into account that the source data streams will not only have different formats, but that they will arrive with different cadences, even in bursts, and it is necessary to treat them properly.

To these three characteristics, different analysts usually add two more:

Truthfulness: As they say “Garbage in, Garbage out”, if the data you enter is not good, what you get from it will not be either. And since the ultimate goal of analyzing all this data is to make decisions that affect the company’s strategy, such data must be reliable. For this it is necessary to verify the origin of the data and eliminate the incorrect ones, to obtain quality data.

Value: The ultimate goal of any Big Data strategy is to generate value for the company, based on more thorough and thorough analyzes. It is this V that is truly important in Big Data, as it is the one that provides business insight.

The  Big Data Training Institutes In Bangalore provides a deep understanding of the Hadoop framework, including HDFS, YARN, and MapReduce, and you will also learn how to use Hive to process and analyze large data sets and Sqoop for data ingestion. In it you will learn through theoretical and practical lessons and you are ready to apply the concepts in your day to day. If you are looking for big data training institute in Bangalore choose the best who can guide you to reach your goal.

Is python programming Object oriented language?

The  Python programming language  is object oriented and is very simple to use while saving all its power. Of  open source , you can find it on your own site. Keep in mind that it is a language comparable to others such as  Perl, Scheme or Java , but due to its characteristics it is becoming the  favorite  for many. Those who work with python believe that it is more  elegant, clean and minimalist.

With  Python  you can program in  scripting , so use an  interpreter  instead of compilation. This is an advantage for you, since you will save a lot of time. Although it is the  opposite of Perl , it also uses the  interpretation of the code  written on the screen to execute the program in question. However, the difference is that it has a greater and  wider variety of  very useful standard modules according to your objective.

Python features..

Simplicity,  accuracy in synthesis ,  good readability , to be able to program  complex algorithms  in a few lines and also use  dialects , some variants adaptable to other languages . However, if  you are new to python  take Python Course In Pune and immerse yourself once and for all in this wonderful “new way” of programming.

What is Python for?

You can program in several styles within the so-called  multiparadigm programming : structured, functional, object or aspect oriented. However, its main benefits go beyond those possibilities of  web development . This  software  is very versatile and useful for  process automation in  order to save you complications.

If you work with  large volumes of data , the  Python programming language  is perfect because processing and extraction in that sense is effective. It can also serve you to  create videogames  because of its dynamism or even have its  extensive library of resources . By placing special emphasis on  mathematics it  is a very good option for  specialized programmers. You are one of them?

So you should not think twice for choosing python course in pune. It is an excellent idea to immerse yourself in the concepts that allow you to master this wonderful language and all the possibilities that a solid knowledge of its main attributes can offer you.

What are the differences between Big Data and Data Science.

This is another thing we should know before choosing to study data science. Although both terms are associated with a large amount of data, the difference between the two is generally not clear. They are certainly related but they are not the same at all. Here are the differences between Big Data and Data Science:

Big Data aspects

  • It involves computations distributed on many servers.
  • Intermingles the processing with the data management.
  • Provides faster and more accurate results.

Aspects of Data Science

  • It involves knowledge of different fields of studies.
  • Take into account all computational aspects.
  • It includes scientific techniques for data analysis.
  • It involves mathematical and statistical theories and analysis.
  • It involves Machine Learning or Automated Learning.
  • It involves the creation of prototypes for software development.
  • Make complete and detailed analyzes of huge amounts of data in a very short time.

Why study Data Science

Today the world is changing thanks to all the technological innovations that arise as a result of data collection, analysis and storage. For example, applications such as: Google Maps, Uber, in addition to all the different social networks such as Snapchat, Instagram, Facebook and also email accounts, make use of the data.

Thanks to data science, airlines can offer better rates to their customers. As well as it has allowed medical science to automatically analyze all kinds of radiological images of different patients.

Studying data science is taking a step to become not only a professional with great skills in computer science, programming, computing and statistics, but also a great data analyst who knows how to understand all kinds of business problems and address it with Fast, real and effective solutions.

In other words, studying data science is studying all kinds of analytical techniques and skills for solving problems in real environments. In addition, you will also train with communication skills, which will allow you to interact effectively and efficiently not only with technology teams but also with clients and work groups.

As a data scientist, you will be in the middle of all this:

  • Access to consumers worldwide, thanks to smart phones.
  • Faster computers and lower storage cost.
  • Smarter algorithms that allow you to work with unstructured data.

How to become a data scientist

If you decided to study data science it means that you feel love for mathematics. That is, you must be good with them, so you must also have a passion for statistics. To become a data scientist you need to adopt an algorithmic thinking and know what data visualization means.

By studying data science you will learn solid business knowledge and acquire an analytical mind that you will need at all times to be a data scientist. Finally, you will need to know tools such as:

  1. Microsoft Excel
  2. SQL
  3. Python
  4. R programming language

And Big Data tools like:

  1. Hadoop
  2. NoSQL

If you have already immersed yourself in all these things, then you are undoubtedly prepared to become a data scientist. You can take that big leap into the new digital world and start studying data science.

The candidates who are looking to work and working already with top renewed companies has to be clear with the hadoop technology as a hadoop developer. Mostly the developers who are working on this technologies they are still struggling for the perfection to fill this gap take big data training in Bangalore be ready. Big data traininmg in Bangalore will help you to be confident on the technology which you are working.

Wanted to become Big Data Engineer?

The IoT pledge is increasingly becoming reality. With 9.7 billion networked devices that are estimated to be in service by 2020, now is the time to optimize big data in your business. These devices – including portable health meters, city electricity meters, smart retail signage applications, etc. – rely heavily on optimized big data.Unorganized data leads to unreliable data sets, insights and devices, which in turn leads to bad business decisions. In the end, consumers will suffer.

The goal of real-time data is to reduce the time between an event and the resulting useful insight. To make more informed decisions, organizations should try to reduce the time between knowledge and benefit as much as possible. With Apache Spark Streaming , companies can run real-time data analytics .

Some big data management challenges include complex technologies, limited access to data lakes , fast value-added generation, and rapid delivery of information.

By the machine learning constantly new methods of data-driven prediction develop. In fact, organizations could not possibly manage huge amounts of big data without big data software and service platforms . Machine learning algorithms can filter out the massive amounts of data that can then be analyzed and used for high quality decisions. Companies should use this technology nationwide to get as much out of their big data as possible.

Big data technologies are constantly evolving. To keep as much as possible from their data in a technologically dynamic environment, organizations need to keep pace with this rapid change.

To be able to switch flexibly between different platforms, first have to reduce potential problems to a minimum. In this way, the flexibility of data and its adaptability to future technologies can be improved. The Big data technologies is ideally suited to solve potential problems.

With traditional storage models, data is slow to retrieve, often resulting in high processing latency. To reduce processing time, companies need to move from slow disks and relational databases to in-memory computing software. A good example of an in-memory storage model is Apache Spark.

It is always better to analyze data before making decisions or taking concrete action. Historically, years of historical data were used to analyze trends, but with the availability of up-to-date data-both batch and streaming data-organizations can now identify trend shifts in real time. In any case, large amounts of cutting-edge data will give businesses a much better opportunity to generate accurate, comprehensive insights.

Big data is synonymous with Hadoop these days. Hadoop is an open source tool that is used to manage large amounts of data and analyze them, so that the knowledge acquired can be applied to make intelligent and calculated business decisions. Hadoop presents an easy and convenient way to manage disparate data and make sense so that people can obtain useful information to improve productivity and business growth. The best way to obtain enormous benefits from this technology is take a Hadoop Training In Pune to obtain a Hadoop Certification and maximize the benefits of Hadoop in your organization. Big data hadoop training in pune will help you to get required knowledge for IT Jobs.

Is python programming really flexiable to work?

Python is very simple to use, but it is a real programming language, which offers much more support for large programs than shell scripts or that batch files can offer. On the other hand, Python also offers much more error checking than C , and, being a very high-level language, it has integrated high-level data types, such as flexible arrays and dictionaries. Due to its more general data types, however, many things are at least as easy in Python as in those languages. If you are looking to take python training choose Python Courses In Bangalore for your excellent career.

Python syntax is super recommended, especially for people who have just programmed, since it is very easy to understand, compared to other programming languages, which are much more complicated.

Python Courses In Bangalore improves and makes your programming much easier for you, in many situations when working on a computer.

Python is capable of threading and processing GPU ( Graphics Processing Unit ) like any other language. Most data processing modules are actually only wrappers ( wrapper ) of Python around the code C / C ++ .

Python allows you to divide your program into modules that can be reused in other Python programs . It comes with a large collection of standard modules that you can use as a basis for your programs, or as examples to start learning to program in Python. The modules are code Pre-written Python that  ” matters” in your Python program . Because there are many tasks that people usually do, there are modules that people have written that do these tasks for you, and generally do them in the cleanest and most efficient way possible.

when you have a Python container around the C ++ code , what someone has done is write a Python code that interacts with the C ++ language. This allows you to make use of various aspects of the language that is being involved, in this case C ++ , without really needing to know or understand that language.

The Python interpreter and the extensive standard library are available for free in source or binary form for all major platforms from the Python website , and can be freely distributed. The same site also contains distributions and pointers to many free third-party Python modules, programs and tools , and additional documentation.

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