big data

Big Data and How it Can Benefit Your Business

Big data can be categorized into four different aspects: Volume, Variety, Velocity, and Value. Let’s look at each of these factors in more detail. Each of these characteristics can be used to improve a business’ performance. If you’re unsure about whether your business can benefit from big data, read on. These four concepts can help…

What is Big Data?

In an era that is driven by digital data storage in the paper format of each organization It might be something that slows down the work. Because now all data can be stored on the cloud, which is a huge storage that can be accessed from anywhere, anytime. In this article, let’s get to know…

What is Big Data? Big data defined What exactly is big data? The definition of big data is data that contains greater variety, arriving in increasing volumes and with more velocity. This is also known as the three Vs. Put simply, big data is larger, more complex data sets, especially from new data sources. These data sets are so voluminous that traditional data processing software just can’t manage them. But these massive volumes of data can be used to address business problems you wouldn’t have been able to tackle before. The three Vs of big data Volume The amount of data matters. With big data, you’ll have to process high volumes of low-density, unstructured data. This can be data of unknown value, such as Twitter data feeds, clickstreams on a web page or a mobile app, or sensor-enabled equipment. For some organizations, this might be tens of terabytes of data. For others, it may be hundreds of petabytes. Velocity Velocity is the fast rate at which data is received and (perhaps) acted on. Normally, the highest velocity of data streams directly into memory versus being written to disk. Some internet-enabled smart products operate in real time or near real time and will require real-time evaluation and action. Variety Variety refers to the many types of data that are available. Traditional data types were structured and fit neatly in a relational database. With the rise of big data, data comes in new unstructured data types. Unstructured and semistructured data types, such as text, audio, and video, require additional preprocessing to derive meaning and support metadata. The value—and truth—of big data Two more Vs have emerged over the past few years: value and veracity. Data has intrinsic value. But it’s of no use until that value is discovered. Equally important: How truthful is your data—and how much can you rely on it? Today, big data has become capital. Think of some of the world’s biggest tech companies. A large part of the value they offer comes from their data, which they’re constantly analyzing to produce more efficiency and develop new products. Recent technological breakthroughs have exponentially reduced the cost of data storage and compute, making it easier and less expensive to store more data than ever before. With an increased volume of big data now cheaper and more accessible, you can make more accurate and precise business decisions. Finding value in big data isn’t only about analyzing it (which is a whole other benefit). It’s an entire discovery process that requires insightful analysts, business users, and executives who ask the right questions, recognize patterns, make informed assumptions, and predict behavior. But how did we get here? The history of big data Although the concept of big data itself is relatively new, the origins of large data sets go back to the 1960s and ‘70s when the world of data was just getting started with the first data centers and the development of the relational database. Around 2005, people began to realize just how much data users generated through Facebook, YouTube, and other online services. Hadoop (an open-source framework created specifically to store and analyze big data sets) was developed that same year. NoSQL also began to gain popularity during this time. The development of open-source frameworks, such as Hadoop (and more recently, Spark) was essential for the growth of big data because they make big data easier to work with and cheaper to store. In the years since then, the volume of big data has skyrocketed. Users are still generating huge amounts of data—but it’s not just humans who are doing it. With the advent of the Internet of Things (IoT), more objects and devices are connected to the internet, gathering data on customer usage patterns and product performance. The emergence of machine learning has produced still more data. While big data has come far, its usefulness is only just beginning. Cloud computing has expanded big data possibilities even further. The cloud offers truly elastic scalability, where developers can simply spin up ad hoc clusters to test a subset of data. And graph databases are becoming increasingly important as well, with their ability to display massive amounts of data in a way that makes analytics fast and comprehensive. Big data benefits: Big data makes it possible for you to gain more complete answers because you have more information. More complete answers mean more confidence in the data—which means a completely different approach to tackling problems. Big data use cases

Companies like Netflix and Procter & Gamble use big data to anticipate customer demand. They build predictive models for new products and services by classifying key attributes of past and current products or services and modeling the relationship between those attributes and the commercial success of the offerings. In addition, P&G uses data and analytics…

Big Data workflow

1. Storage (Storage) It is the process of collecting information. all from various sources whether it is quality information, including expected information that may be useful; Whether it is text data, document files, image files, video files, audio files that are recorded will be collected here 2. Data Processing (Processing) data processing After the data…

Big Data workflow

1. Storage (Storage) It is the process of collecting information. all from various sources whether it is quality information, including expected information that may be useful; Whether it is text data, document files, image files, video files, audio files that are recorded will be collected here 2. Data Processing (Processing) data processing After the data…

What is Big Data and what can it be used for?

Big Data is a term that is widely used in business circles. Because digital technology is advancing to its greatest extent today. Important information has been created enormously Waiting to be further developed for endless business opportunities. Let’s get to know Big Data. How important are these data sources? And how can it be developed…

Big Data Analytics and Online Marketing

If you’ve ever had a hard time analyzing data sets, you’ve probably heard of big data. It’s the field of data analysis that deals with datasets too large for traditional software. This is where advanced algorithms come in. These tools will analyze massive amounts of data and provide valuable insights. If you’re unable to process…

Big Data Analytics and Online Marketing

If you’ve ever had a hard time analyzing data sets, you’ve probably heard of big data. It’s the field of data analysis that deals with datasets too large for traditional software. This is where advanced algorithms come in. These tools will analyze massive amounts of data and provide valuable insights. If you’re unable to process…

Characteristics Of Big Data

Big data can be described by the following characteristics: Volume Variety Velocity Variability (i) Volume – The name Big Data itself is related to a size which is enormous. Size of data plays a very crucial role in determining value out of data. Also, whether a particular data can actually be considered as a Big…

Big Data and How it Can Benefit Your Business

Big data can be categorized into four different aspects: Volume, Variety, Velocity, and Value. Let’s look at each of these factors in more detail. Each of these characteristics can be used to improve a business’ performance. If you’re unsure about whether your business can benefit from big data, read on. These four concepts can help…

  • 1
  • 2