Big Data Write for Us
Big Data Write for Us – Big data refers to data sets that are too large and complex for traditional data processing and management applications. This term has become famous thanks to the rise of mobile technology, IoT (Internet of Things), and AI. Indeed, these devices and services, such as geolocation, social networks, mobile applications, or the management of web browsing history, product more and more information that needs to be managed and processed efficiently.
Therefore, the term “Big Data” refers to the process of collecting and examining massive amounts of digital information. It is part of Business Intelligence (BI) in the business sector. This process makes it possible to put data and the digital ecosystem at the service of teams, sales, and marketing, and if you can send us the ideas and submit the article, contact at contact@technostag.com.
What is Big Data Used For?
Big data is an essential tool for B to B and B to C companies. The data collected helps them craft personalized marketing campaigns tailored to consumer needs, preferences, and behaviors. This information helps to improvement the customer experience, attract prospects and retain existing customers.
Big Data and Data Storage
The rise of big data has followed the evolution of data storage and processing systems, particularly the advent of cloud computing and supercomputers. From now on, we speak of petabytes and zettabytes to designate the volumes represented by big data. According to forecasts by IDC, the importance of data produced worldwide will reach 40 zettabytes in 2020.
How does Big Data Work?
Big data makes it possible to meet a vast technological challenge: storing a large amount of data from different channels on a massive hard disk, easily accessible worldwide. Data is stored in a safe place and recoverable at any time in the event of any incident. The files are cut into several fragments called “chunks” to achieve this. These fragments are then distributed over several computers, and there are different ways to reconstruct them.
History of Big Data
Although the concept of big data is relatively recent, the appearance of extensive data sets dates back to the 60s and 70s. At that time, the first data centers were coming out of the ground, and relational databases were slowly appearing. In 2005, users knew how much data users generated on Facebook, YouTube, and other online services. Hadoop (an open-source infrastructure explicitly created to store and analyze big data games) was developed that same year. NoSQL also began to be used more and more at this time.
Big Data Challenges
While Big Data opens up exciting prospects, it nevertheless presents certain pitfalls.
First, Big Data is big. Although new technologies have been developed for storing data, data volumes are doubling approximately every two years. Businesses still struggle to control their growth and find ways to keep it efficient.
But it is not enough to store the data. To be valid, these must be exploited and, upstream, organized. Clean data, or data relevant to the customer and arranged to enable meaningful analysis, takes a lot of work. Data scientists spend 50-80% of their time organizing and preparing data before it is used.
Big Data and Data Storage
The rise of big data has followed the evolution of data storage and processing systems, particularly the advent of cloud computing and supercomputers. From now on, we speak of petabytes and zettabytes to designate the volumes represented by big data. According to forecasts by IDC, the importance of data produced worldwide will reach 40 zettabytes in 2020.
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