Nowadays society is able to produce and collect in one week the amount of data that used to take years. Without noticing, we produce hundreds of data daily just by entering the internet. Or checking the social media and playing from the cellphone. So lets understand the relevance of Big Data.
What is Big Data?
It is the analysis and treatment of a wide volume of data. Large amounts that result in practically impossible to try it manually. Or in the conventional analytic.
The study of these data groups will work as a support to make more accurate decisions. For this, it is necessary to have an aim in the company and establish a clear and logical way to accomplish the proposed objectives through analysis.
In the current article you will get to know deeply the true value of Big Data. Its main contributions, its uses, how to implement it in your business. And some examples of successful cases. Topics we hope will be very useful.
Main Big Data’s contributions to Enterprises
How can Big Data contribute positively to companies? The answer is by rising competitiveness. The one that is reflected on the following aspects.
- Operational risks reduction by improving decision-making. Regarding the market products. Actually, some companies have incorporated sensors in their products. To get information related to their consumers. For example their likes, among others. Improvise is not an option.
- Effective and immediate product’s evaluation. Thanks to the compilation data systems produced in real time and storage in databases to be analyzed. What does not work is removed or changed.
- Personalized actions and costumers. By obtaining more accurate information of the specific markets and developing products adapted to your needs.
- Communication improvement in the company. By providing adequate diffusion channels of information. And by optimizing the data quality, noticing more agility, effectiveness, and productiveness in the processes.
Big Data Uses in the industries
Even though objectives, goals and obtained data vary significantly from industry to industry, Big Data carries on its implementation for different uses, industries and sectors. We can see some of them below:
Energetic sector and public services:
- Renewable energy production prediction to manage the resource adequately and help the planet’s conservation.
- Data analysis for failure detections and preventive maintenance.
- Prediction of the energy consumption to handle the demand and offer.
- Frauds detection in the users’ consumption to implement safety measures that minimize the crime execution.
- Definition of consumption patterns vs energy generation to carry out diagnoses that derive from responsible consumption and an efficient production.
Retail:
- Listening platforms based on Big Data, where the social media flows filter and analyze certain key words or consumers’ feelings toward the brand, to know the positioning in order to make adequate decisions.
- Visitors’ prediction to know the user’s movement and predict with more certainty where to open them.
Industry and manufacture
- Forecasting inventory to optimize the production process.
- Monitoring the machine’s performance for failure prediction and preventive maintenance.
TIC’S:
- Tracking the website’s performance and usability.
- Analysis of large volumes of data from digital marketing campaigns to predict the new products behavior.
Banking:
- Trend analysis to make investments more effective and profitable.
- Analysis of information to know where to place an ATM.
- Visitors prediction to close or place new sites.
Other sectors:
- Advertising agencies use it to design more specific and faster marketing campaigns.
- Fashion designers use it to follow trends and create more innovative products.
Steps to implement Big Data
Most enterprises handle such amounts of data that would result impossible to manage it traditionally. To satisfy this need comes Big Data, allowing to carry out effective analysis of large volumes of information for assertive decision-making. To obtain the biggest success will depend on the organization’s implementation. That is why it is necessary to define the following steps:
- Business objective: We must identify the problem and look for ways to achieve the goal. Fundamentally, we will seek to reduce costs and increase revenue.
- Veracity and integrity: the data sources that we use for our analysis must be reliable, truthful, dynamic and updated.
- Analysis implementation: it is relevant to determine which tools we will use to analyze the data and what relation it has with the established objective.
- Analysis introduction: we need to previously know our current clients’ profile, the same as the potential clients, the ones we are aiming at. If we have a concrete analysis and objective, we must be able to anticipate the clients’ reaction.
- Plan execution: the implementation and execution procedure are constant procedures that require revision, analysis and improvements in those parameters that are incorrect. This is an alive process that activates from minute cero when the analysis starts.
- Distribution of the information: once the analysis is carried out, it will not work if we do not send the information to the heads of each affected unit for decision-making and actions.
- Innovation: the disruptive progress is generated the moment the company changes the chip, improves and applies the acquired knowledge through innovative processes.
Successful Cases
Currently, the use of Big Data is in many operations of our life, for instance, when we make a home order, when we use Waze, Spotify and Netflix, when we ask for an Uber or when any platform makes a recommendation based on our preferences. How do big companies implement this science?
Starbucks Case
Have you ever wondered how Starbucks can open so many stores in such a small radius and still has all its stores full? The answer, the use of Big Data where they determine the potential success of each new store by collecting information about location, traffic, demographic area and consumer behavior.
By doing this type of analysis before opening a store, Starbucks can make a fairly accurate estimate of what the success rate will be and choose locations that meet the established parameters.
Coca Cola Case
Big Data has allowed the soft drinks’ giant to improve from its bottling plants to the operation of its dispensing machines.
How was the flavor “Cherry Sprite” born? Thanks to the analysis of data in areas such as product development, where the data collected from dispensing machines allow consumers mixing their own drinks, Coca-Cola was able to identify the most popular blend and turn it into a ready-to-drink beverage.
As we can see, any company’s future is in Big Data or data analysis. Some years ago, it was impossible to predict market behavior and it should be assumed based on the past, but today the future is almost assured thanks to Big Data.
At Interfaz, we have the experience and the most prepared staff to accompany you and give the big step through Big Data, so you can take a remarkable advantage over the competition. Contact us with no hesitation.
If you are considering the implementation of Big Data, you have to understand it as a tool to increase competitiveness, not a collecting data element.
