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