What is Big Data Technology?

What is Big Data? The answer is staggering. It is simply a new way of collecting, organizing and analyzing data. A new software tool to scan, process and analyze the huge amount of unstructured and structured data which cannot be processed traditionally or even manually is known as Big Data Technology. This implies that Big Data is more than simply storing information in your computer – it is also about gaining insights on how the world works and what can be done to make life better.

what is big data technology

As opposed to the old-school concept of IT investments in servers, storage and network infrastructure, today’s IT leaders are focusing on the ability to generate, analyze and leverage large amounts of data using a minimal IT footprint. IT leaders are starting to use advanced frameworks such as software-as-a-service (SaaS), cloud computing, and data visualization technologies to help them achieve this. To be successful, these new technologies require an open, collaborative approach across the entire organization. In other words, big data technologies are changing the foundation of how organizations collect, manage and analyze information and are changing the definition of IT itself.

Let’s take a closer look at some of the emerging technologies in this new fabric. One such technology is social media marketing. Companies like Google, Facebook, Twitter and LinkedIn have been collecting information about their users for years and are now using this information to deliver personalized services to consumers. Another popular technology is visual media, such as 3D maps, aerial photos, and action movies. Data from these sources can also be used for strategic data creation, such as understanding what neighborhoods and communities work best for specific purposes such as education, jobs and shopping.

Data visualization is one of the big data technologies of the 21st century. This refers to creating visual representations of data in a manner that is easy to understand and explore. Examples include GIS, visualizations, cartograms, heat maps, tensors, matrices, or neural networks. Machine learning is another term you may have heard before. Machine learning refers to using supervised artificial intelligence (AI) techniques to create software that can recognize patterns, make predictions and even act on those predictions.

Cloud computing is the foundation for many large scale data processing applications, such as e-commerce websites and big data analytics. The key difference between cloud services and the web services that we use every day is the fact that the latter do not run on the user’s computer, but rather on a virtual server. This virtual server is hosted by a third party and the user gets all of the resources on that server, including the network, storage, power, etc., for a fixed monthly rate. With today’s hosting prices, cloud services make a lot of sense.

Some popular open source solutions that go beyond simple file and report ingestion are Mongoose, Hadoop, Spark, and Json Script. Of course, the first two will make more sense if you look at what each product does. Mongoose is an open source project started at Facebook that provides a framework for efficiently managing complex data structures and tasks. It makes the job of building a database much easier by providing a model, a vocabulary, and a collection manager. Hadoop is another open source project started at Facebook that provides a platform for handling large amounts of data efficiently.

In addition to the cloud-based offerings from the aforementioned technologies, PrestoLite from IBM offers an easy way to ingest complex data sources and store them efficiently. PrestoLite supports the popular Presto format for BigDatus and works seamlessly with the Python, PHP, and Java platforms. The company that developed PrestoLite, IBM was one of the first to implement the XML Schema layer on top of the Open Database Language (OWL). This layer is what gives the product its ability to scale up to large volumes of streaming data without requiring the developer to change their server architecture significantly.

With all the advances in programming language technology and frameworks such as python and Spark, it has become much easier for applications and websites to scale up and run rapidly. This has given rise to the development of several different tools that help web developers and IT managers visualize and manage the data sets they have to deal with. The technologies like Hadoop, Spark, and PrestoLite aim to provide an open source solution for managing the large amount of data sets necessary for successful enterprise development. While the tools are not specifically designed for mobile apps and gaming, their ease of use and flexibility make them very appealing to the end user.