To start this conversation, let’s define what the term “date” is, after all? From this, we will be able to better understand the dimensions that exist between small, big data. Date, are the available records of a system, capable of generating information.
Think, for example, of a store’s sales records. First of all, these records must be in a physical or virtual location. Therefore, if these records are complete, they can provide important information about the store, such as the quantity of products sold, daily profit, expenses, etc.
If these records are not organized, no useful information can be extracted from them. So the data alone doesn’t say much. They have to come along with other data, which will add value to these records.
In these parts it is a little easier to think what are big data and small data?, Not? Big data has a lot of data and small data has little data. But this is partially correct.
when size becomes a problem
big data it’s not just about big data, but also when data volume is an issue. And with this problem two more arise: speed And variety. So we have, what is called, 3vs of Big Data.
The volume issue ﾠ
For example, let’s go back to the shop from the beginning. The management has decided to take over the services of _dreamlabs. So, thank you for yours technological solutions, has become a network of stores distributed throughout the cities of Brazil.
So your data record is bigger. It needs more storage space. In addition, you will also need more speed. Which brings us to …
The question of speed
Recording the sale of 5 customers a day is a simple task. But the registration of 1000 customers per hour is not. You will need software that can analyze and respond to this information in real time.
These records are important for running the business. In addition to indicating unnecessary expenses. In short, they are critical to the success of the company.
So far we have talked about it structured data. Data sorted in tables and columns that indicate clear and objective records.
the question of variety
The store therefore wants to launch a new product. But first, he has to evaluate the market. Do you need to know what your customers think about the company? What innovation can it bring to the market? This will help you gain a competitive edge among competitors.
It is not enough to analyze only the internal data. He will need different data from his customers. This data is available in different formats, images, text, video, audio and so on. And right now, the third V of big data, the variety.
In addition, a large database and a set of tools capable of collecting and analyzing them are required to carry out this investigation. unstructured data.
In this way, the information will bring knowledge, the intuition necessary, ensuring the most successful launch of a product on the market.
Big Data is the brain
However, big data it is not just a question of the market. It can be useful for a number of areas. Since when astronomy, as far as artificial intelligence. We are only at the tip of the iceberg!
Like this, big data has problems with processing power, storage and organization. While 1GB was a large amount of storage before, it doesn’t mean much today. With the technological evolution there is an exponential increase in users. In parallel, there is the development of new data analysis technologies provided by these users.
Thus, the 3 “V” of Big Data they present themselves as a problem when it is not possible to account for so much data. Hardware and software support is needed, which will function like a brain, capable of processing and storing valuable information, previously lost in the sea of virtual data.
Big Data vs Small Data?
Everything is data! Data underpins both approaches. In this regard, they are complementary. But they are different approaches.
Small data, operates on the opposite side of 3vs of big data. Less data, slower and with far fewer variables.
After a lengthy interpretive analysis, this data will influence decision making, whether from an AI or a marketing campaign.
When size is an advantage
if in Big data, the volume becomes a problem, in Sshopping center data, it can be an advantage. Dealing with less information increases the chance of getting better strategies.
Let’s go back to the shop at the beginning of this article. Let’s assume that after collecting valuable data through the analysis of big data, feels the need for another strategy. So, he intends to take specific action, to solve specific problems in a store.
This time it will send a marketing team to the store with problems to come back with exclusive solutions from that region.
Through extensive research in the field, they come to a conclusion: that shop is not part of the daily life of the inhabitants as it is a shop out of town.
Your competitors are no other big stores. These are small local shops that are more trusted by the public as they are located within the community.
This intuition it’s thanks to what you might call Small data. Quality information that leads to specific decisions for a particular problem.
Small Data is the heart
It is almost inevitable to make this comparison. big data it’s a logical process, Small data it’s an intuitive approach. But one does not exclude the other. In reality, one does not exist without the other.
It is not possible to make an important decision alone big data. Small data, further refine the data to maximize all available information. Both increase the chances of success of any action.
Conclusion
Two sides of the same coin. Big Data and Small Data, they are present daily in our life. We constantly feed data to networks. Hence, as we provide valuable information for every survey we respond to.
Better connections generate better information and, therefore, are ready to be used to improve the user experience and the success of a business.
Finally, since we’re here, how about doing the same for our item shop? Contact the _dreamlabs! We can make your idea take on a new dimension!