Full Stack Big Data

As business organizations are building more diverse and user-centric data products and services, the demand for machine learning is growing rapidly for predictive insights, personalization, and recommendations. Earlier, data scientists were able to solve these problems using popular tools such as Python and R. But as companies are producing and amassing a large amount of data, data scientists are spending a major portion of their time supporting their data infrastructure rather than creating the models to solve data problems.   To help in solving this problem, Apache Spark offers a general machine learning library known as MLib, which is exclusively designed for simplicity, scalability, and quick integration with other tools. With the scalability, speed and language compatibility of Apache Spark, data scientists can solve and iterate through their data problems easier and faster. Undoubtedly, MLlib’s adoption is growing very quickly as can be seen through the large number of

If the title of this post interests you, the chances are high that you are planning to make a career in the field of big data. As the big data world is growing very fast, where you end up in it mainly depends upon your first step. Fortunately, we are going to start from scratch and give you a complete guide to pursuing a career as a big data architect. Before diving deep into the subject of big data architect, let’s take a sneak peek at what’ll get covered in this post. ·          Who is a big data architect? ·          The job description of a big data architect ·          The necessary qualifications for a big data architect Who is a big data architect? In the computer science world, ‘architecture’ means building computer systems. The “systems” can be large and complex, and to keep them running, you should strictly follow a list of rules and methods.  In other words, a big data architect is a person who comes up with certain rules and methods and meticulously implies them

In this digital era, a single click of the mouse on the “Agree” button can provide enterprises complete access to almost all your information. For many business organizations, collecting user information is vital to be able to send the most personalized messages to its customers.   Today, big data has become a fundamental part of communication and marketing efforts to augment value for businesses – as shown by Netflix and Spotify, which have utilized their huge user data to create engaging messages for their targeted audience.   However, this has caused fury amongst those who think that if you are using personal data without adding any value, it’s annoying, not amusing. Owing to the frequent misuse of information and data leakage, there is a growing fear for privacy and security of the data. The advancements in technology are bringing myriad opportunities and possibilities for businesses, but how well are they prepared for the potential risks associated with data use?   Sm

Big Data is present everywhere, or we can also say that big data is leading the IT revolution from the forefront. Ride on big data, and you can move high in your career graph. These days, a large amount of data is being produced by business enterprises almost every day. But if you don’t know how to leverage this voluminous data, the chances are that you are leaving money on the table. This is where big data analytics comes into action. Big data analysts help in improving the business decision-making process and give your organization a competitive edge over others. With more and more business organizations understanding the importance of big data analytics as a useful source for making informed business decisions and gaining actionable insights, the demand for big data analysts is going to surge dramatically in the coming years. If you are still unsure how big data will give your career a head start, listed below are some top reasons to clear your doubts.   1. The demand f

You got a big data project. You understand all the ins and outs of the domain, and probably you’ve decided what framework you will use or what infrastructure to use to process all that data, but if you are confused about which programming language to employ for your big data project, this post is for you. Though there are many options to choose from -- Java and Python to R and Scala, picking the right programming language for your big data project can make a big difference between a highly successful project and one that only scratches its potential.  Here's a quick rundown of each programming language to help guide your decision #1 Python The field of big data and data science being relatively new, many erudite folks are to be seen constantly debating about the pre-eminent programming language for big data.  You might know that Python has been present for over a decade, and is more popular in academic circles. Its forte lies in Natural Language Processing (NLP). If yo

In the realm of big data and analytics, a certification in Hadoop is something that can bring you not only a high-paying job, but also a smooth gateway to success. If you earn a certification in Hadoop, finding employment in a leading business organization and climbing the ladder to the top position in your organization becomes easier. Now, let us try to find out why certification in Hadoop is such a big thing in the realm of big data and analytics. The primary reason why Hadoop certification is gaining popularity is the ubiquitous presence of big data. Today, big data is invading almost every industry vertical from media and healthcare to engineering, retail and even government services. You might be familiar with the Forbes 2015 report, which says that around 90% of global commercial institutions are investing profoundly in big data and data analytics, which can drive huge returns on investment, giving you a big reason to get a Hadoop certification. Moreover, did you kno

Machine learning has got off the ground and it’s taking every industry by storm, bringing new insights to businesses that aid them in taking result oriented actions. If you want to be in demand, you need to learn this skill in order to separate yourself from mere data analysts. Getting started with machine learning can be intimidating for many of us, but it’s surprisingly easy to learn machine learning if you approach it in a right manner. Believe it or not, Machine learning (ML) is a compelling field of study that’s why it is quite easy for a novice to get fascinated. It’s what that has given birth to handwriting recognition, face recognition systems, self-driven cars, navigation systems of drones of all kinds, robots that can clean your house, or the recommendation system behind YouTube and Netflix. Before Starting, a Word of Caution for beginners Machine learning (ML) is a vast field of study and is something of an advanced practice, and you’ll need to have not

The world is going digital, and this simply indicates that big data is here to stay. In fact, big data is present all around us, and there is an urgent need to gather, sort, and analyze whatever data is being generated, since data is the new oil. The importance of data analytics and big data is only going to increase in the coming years. You might know that big data is a technology-driven approach that is widely used to evaluate complex data sets to arrive at key decisions. Thus, we can say that big data is a smart career choice and it could be just the right type of career you have been looking for. Those who are working in the field of data science can expect a handsome salary, with the median salary range for big data scientists around $116,000. Even those who are working at the entry level as a data scientist can expect average earnings of $92,000. As more and more organizations realize the need for data scientists and big data analysts, the number of jobs will continue to gr