Think about the amount of data that is generated on a daily basis . This ranges from the exchange of emails, information on the web such as posts, videos and images, and the exchange of messages through applications such as Telegram, WhatsApp and Facebook Messenger.
Let's take all this data, organize it, analyze it, and study behaviors and trends. Then it becomes easier to understand grandes datos .
Big data is structured and unstructured data that is generated daily by companies, that is, they are enormous volumes of data that are generated every second.
Organizing this data is what makes grandes datos a big step, since the combination of technologies allows this volume of data to be managed to achieve real-time analysis, which can bring numerous benefits to companies.
oh great data It is characterized by three “V”s:
Volumen: amount of data captured. Reference sources can be diverse, such as social networks, message exchanges, purchasing information, banking data, etc.
Speed: The speed at which data is processed and transmitted. This process must be agile christmas island businesses directory so that this information is processed as quickly as possible, in real time so that decisions can be made quickly.
Variety: It is related to the generation of data, which can be structured or unstructured.
There are businesses that take into account other points, such as variability, value, veracity (authenticity) and complexity.
How important is big data?
Data cross-referencing allows us to gain multiple perspectives . Today's consumer is increasingly demanding and has many more options for products and services. The better the data analysis, the better the needs of this consumer will be met.
Oh grandes datos allows you to obtain precise information, extract the needs, dissatisfactions and desires of customers, generating value for the business.
Data structuring
As we mentioned, there are two types of data: structured and unstructured. Structured data is data that has a defined structure, with categories and definitions, such as location and customer profile.
Unstructured data is the data you need to be prepared for, it is the raw data. This could be data from social networks, for example, such as Facebook , Instagram , YouTube and LinkedIn , which require complex data processing, such as videos, texts and images.
An example of this is tracking mentions on medios de comunicación social , where a certain keyword can show a sentiment or opinion of followers in relation to a certain brand. This data must be analyzed, since a simple robot will not be able to give a definition to a certain comment.
Existing data types
Basically, there are three types of data in grandes datos : personal information or datos de las cosas (remember the Internet of Things?), business data and cita social .
Personal information or datos de las cosas
In our post Internet of Things: Why you should keep an eye on this trend , we showed how technology is close to our daily lives and how it can impact marketing data.
This data can generate important information, making people's lives easier and helping to understand their needs.
Business data
These are data generated by companies, such as financial data, purchase and sale operations, human resources, etc.
Datos sociales
This type of data is closely associated with behavior. In addition to social networks, we have other channels, such as search engines and cross-browsing habits.
Cross-referencing these three types of data can result in the generation of essential business information.
Big data analytics
This is where grandes datos Analytics comes in. Transforming this data into useful information, using technology as a backdrop, is what will transform these perspectivas into results.
It is important to highlight that the strategic part must be aligned with the technology, which must process the data and transform it into information that can be understood by those who will perform the analysis.
How to apply Big Data
The application of the data will depend on each company. A company, even a small one, that works in a certain region, can collect data by postal code, for example, and cross-reference it with information from Google Maps, for example, to understand customer needs in relation to services and products.
A marketing department can study consumer behavior to implement specific actions or even make changes and tests on its product. Analysis can be done by region, gender, age group, seasonality and other elements that can be extracted from social media, for example.
As we can see, grandes datos can be applied to any type of business, regardless of the area of activity and size. It is extremely important to take advantage of the amount of information currently available, as it allows us to better understand what consumers and our customers need.
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