Have you ever wondered how much information is generated in the form of mobile messages, calls, emails, photos, videos, online searches and music just while we use our mobile phones? An average of 40 exabytes of data per month from each smartphone user. Now imagine the amount of data accumulated by the 5 billion devices used worldwide. What if we add all the national data and company archives? Information with a similar volume - such as ordinary computers can not manage, we call Big Data.
Big Data is increasing the demand for information management professionals so much that software giants such as Software AG, Oracle Corporation, IBM, Microsoft, SAP, EMC, HP and Dell have spent more than $ 15 billion on software companies specializing in the management and analysis of data. In 2010, the industry cost more than $ 100 billion and grew by nearly 10 percent a year, about twice as fast as the software business as a whole.
Big Data is revolutionizing entire industries by changing human culture and behavior. This is a result of the information age and is a factor influencing the way people train, create music and work and, in general, live. Big data is used in healthcare to map disease outbreaks and test alternative treatments. NASA is relying on them for its research, and even utilities rely on Big Data to study customer behavior and avoid service interruptions. They are widely used in cybersecurity in the fight against cybercrime.
Implication and significance
The importance of big data is not in its size or abundance, but in what you use it for. Combining Big Data with powerful analysis can identify the root causes of failures, problems and defects in near real time, detect fraudulent behavior before it affects your organization, and thus prevent financial losses.
The optimizations and changes that are achieved reduce the cost and time to carry out certain processes and entire projects. New products are developed, applications are optimized and goals are set, guaranteeing further success regardless of the field and endeavor.
Each rose has thorns
In general, having more customer data (and potential customers) should allow companies to better tailor their products and marketing efforts, creating the highest level of customer satisfaction. However, increasing the amount of data available presents both opportunities and problems. Companies that are able to collect large amounts of data are given the opportunity to perform a more in-depth and richer analysis. However, the processing of big data can also lead to congestion and unwanted delays.
In addition, the nature and format of the data may require special processing before it can obtain any value. Structured data consisting of numerical values can be easily stored and sorted, but unstructured data such as emails, videos, and text documents require more sophisticated techniques before they can be useful.
Surfing the wave of digital transformation
Digital transformation is the global currency to push technology around the world. Every day, the amount of data that is generated and owned marks a new peak and records another record.
IaaS (Infrastructure as a service) providers have set themselves the goal of continuing this growth by building new data centers every day. From the bowels of the ocean to the polar regions, battling the heat and heating of server rooms - their constant challenge and greatest enemy.
Digital transformation goes hand in hand with the Internet of Things (IoT), artificial intelligence (AI), machine learning and Big Data. IoT devices are expected to reach an astonishing 75 billion in 2025. At 26.7 billion at the moment, it's easy to see where this big data is coming from. Machine learning and AI tools will try to take advantage of the big data extracted from massive data centers, making sense of hidden connections and looking for only the best, fastest or most profitable.
However, corporations have a lot of work to do to optimize the use of all this data on their data servers. In the US economy alone, for example, $ 3.1 trillion is lost annually due to poor data quality. It remains to be seen how companies will deal with this and what decisions will be taken to overcome the problem.
More Natural Language Processing
Big data, AI, IoT and machine learning are reformatting the notion of human and technological interaction. These technologies acquire a human face through natural language processing (NLP).
In the current state of natural processing, it will not take the form of an android or a cyborg, as presented in science fiction movies. Instead, it will help people to participate and interact with various intelligent systems using only human language.
NLP will allow even the most ordinary users to interact with smart systems. You do not need to resort to exotic codes, which is the typical way this is done. It is not just about access to quality information, they can invite the system to give them the idea they need to move forward.
NLP will allow businesses access to mood analysis. This will allow them to know how their customers feel about their brands on a much deeper level. There are many ways in which information can be linked to specific demographics, income levels, educational characteristics and the like, sorted by big data at the same time.
The choice between evolution and extinction - Big Data vs Big Bang
Much of the use of data will be regulated and monitored in both the private and public sectors. As we are now more than halfway through 2020, we can expect further development of big data analysis.
Based on market forecasts, big data will continue to grow. This will affect the way companies and organizations view business information. They need to continue their efforts to adapt their business operations, so they can start optimizing the use of information with analytical software. The goal is to make their business grow while transforming their data-driven environment. Therefore, it is best to keep up with the latest surveys and big data news.