BIG DATA: AN OVERVIEW
13 MAR 2020
The importance of obtaining relevant data for analysis and interpretation with the disruption obtained by the internet following the decade of 2000, the amount of data created started to be disproportionate, making it difficult to measure and interpret them.
In the 90s, BIG DATA emerged as a theme that could define this massive amount of information. The term refers to an extensive set of stored data based on in what we call 5Vs:
We can say that today the world is hyperconnected. According to internetworldstats.com, by the end of 2019, the number of internet users reached 4.7 billion people, which means the generation of data in all its forms is becoming somehow of the biggest challenges people and companies will face soon. How to manage such an enormous volume?
HOW TO COLLECT DATA?
Currently considered one of the critical activities for business success, data collection & analysis became a core activity within the routine of any professional that aims to be updated and competitive. Data Scientists, Business Analysts, Information Architecture – these are just a few in the middle of new job functions emerging every year in the market landscape.
Data collection is related to the act of searching for information on selected topics, performing researches, gathering documents, and evidence through specific techniques.
Research always played an essential role in corporations, collecting valuable information about the market, such as competitors, the economy, and so on. But one of the most significant changes can be seen in digital consumer behavior, drastically impacting the speed and amount with that the data’s generation.
When starting a data collection task, determine your objective first, so it will be more assertive to identify the type of data that you will need for your project coming to life. Remember, it can be in different forms, such as texts, graphics, images, videos, and even voice.
We know that planning is paramount for any business and activity, then structure well each stage of your research, which will help to achieve better results.
It is necessary to have the understanding that quantity is not quality; therefore, you should always focus on data directly aligned with the stipulated objectives. If you pile a lot of data unnecessarily, you will spend a big part of your time having to pan the relevant data in the middle of irrelevant data.
Use technology to your advantage in the process of collecting data, use data mining platforms, software automation, and optimize all stages of the process.
What tools to use?
Currently, several companies serve quite well the market with various solutions. We can mention one of the best known in the digital world, Google Analytics, which collects web search traffic and behavioral information. We also have online forms and questionnaires, specific software, traditional means such as interviews and observation.
How long does a data collection take?
It all depends on how to process the collection. It can be manual, which means hours or even days and nights of stressful work. Or in an automated way, usually performed by software and online platforms, which may take minutes, or even seconds.
The importance of big data analytics
In 2019, Brainstation, a global leader in digital skills education, surveyed thousands of professionals about the primary skills for 2020 and, not surprisingly, nearly 90% of its respondents stated that data literacy would impact the success of their organizations.
Another interesting finding, among data professionals participants, data should be primarily used to optimize existing platforms, and secondly to on innovation of products and services.
The research also envisions that AI is becoming the big thing in the next ten years or so, but also mentioning machine learning and internet-of-things as significant trends as well.
You can access the full survey directly on Brainstation, worth reading it.
WHAT MAKES A RELEVANT SOURCE?
The media and media channels have grown exponentially with advances in technology, which makes us take a particular precaution regarding data and information that appears on the digital network, especially concerning hot topics such as fake news and fake data.
HOW TO EVALUATE IF A SOURCE IS TRUSTWORTHY?
A tip for evaluating the quality of information is to find the source of the source. It sounds funny, but that’s yet a simple way to minimize the chances of being deceived.
Trusted sources always cite other sources, in addition to their reputation. This research model is the most effective
to see if what you’re reading is reliable. The credibility that a source transmits when providing available information is what will count at the time of evaluation. It must preferably have a history of assertiveness and a consistent base.
RELEVANT SOURCE, RELEVANT INFORMATION
Watch out #1 – Where to look?
When we work with information, it is necessary to have in mind where to look for the sources.
It can’t be anywhere. If you are searching something on lawsuits, you will not go to the source that talks about sports, but instead to the official agencies. Having that direction is critical, and you will be most likely to find what you are looking for if you do so.
Watch out #2 – Check, double-check!
The internet has become a world of information, but even if you think you are in the right place, it might not be reliable. Study each source and check if the data made available has some foundation. You can identify inconsistencies by comparing the outputs, and don’t be surprised by what you may find.
By obtaining meaningful data, the chances of deciphering relevant information are higher. Information relevant means minimizing errors hence getting better performance over desired results.
“Knowledge is of two kinds. We know a subject ourselves, or we know where we can find information upon it.”
Data analysis is a process used in different types of businesses aiming to discover relevant information that will help the decision making to be more productive. It may have multiple facets and involves inspection, cleaning, transformation, and finally, modeling.
Through data analysis, it will be possible to identify the necessary information that will be essential for the resolution of the problem in question or to achieve the determined objective.
Data analysis can have different techniques, being them through quantitative analysis, qualitative, categorical, in graphics formats such as pie or circular, columns, and rows. The choice of the graph varies according to what you want to present.
It is necessary to be very careful when analyzing, using logical and rational reflections to reach a consensus.
After data collection, there are no secrets to the analysis, although it requires interpretation and the allocation of information found in each data group collected.
Data collection has been an excellent tool for companies to obtain information that characterizes the behavior of their customers and consumers, analyze competition, demonstrate the performance of projects, and so on.
There is still a significant obstacle in terms of security regarding data collection because many people are afraid that private information and confidential information fall into the wrong hands used for illegal activities.
Technology companies are investing not just in innovations and solutions to reduce the whole complexity generated by trillions of gigabytes created but also in cybersecurity.
Data collection needs to be secure and confidential, people and companies that provide your information need to be aware that there are policy security and privacy, and laws such as the GDPR are shaping the future in that matter.
A good data collection is one that performs all terms of protection of the researcher’s data.
Learn more about BIG DATA:
- More Data, Less Intuition
- How BIG DATA Can Assist In Financial Compliance Processes
- A Step Towards Artificial Intelligence
We hope you find this content useful, and we will be delighted if you keep following with us.
UpLexis® is a company specialized in technologies emerging markets for analysis and interpretation of large volumes of data (BigData) extracted from the internet and other knowledge bases.
Our mission is to provide intelligence for operations a business where relevant information plays a critical role in the exercise of decision-making, in obtaining competitive advantage and improving organizational efficiency.
We bring together talented and skilled professionals for the production of software technology applied to the acquisition, organization, storage and access to information, having some patents in the area.