The use of this trend can enhance the results of companies in the market. However, it is essential to know which analysis model to use in each situation.
The volume of data generated by society does not cease to increase every year, so companies need to modernize their strategies so that they can deal with this flood of information.
But, to use that large amount of content and transform them into insights relevant to business, it is necessary to apply the correct methods of analysis.
When used correctly, Big Data can be a faithful ally of companies, thus helping managers to make decisions so that they can achieve better results. Through the correct analysis, it is possible to measure the results, predict trends, and test scenarios. However, several options can be used to achieve different objectives.
Therefore, to apply them correctly, it is essential to know them thoroughly. Do you want to know what types are available? Continue reading this article:
- Types of Big Data Analysis
- Predictive analysis
- Prescriptive analysis
- Descriptive analysis
- Diagnostic analysis
- 1. Improvement when discovering needs for the company
- 2. Improvement in decision making
- 3. Evaluate the products and services of the company more efficiently
- 4. Customer segmentation to customize actions
- 5. Improvement of accessibility and fluidity of information within the company itself
- 6. Competitive advantages
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Types of Big Data Analysis
The use of Big Data Analytics technologies has become increasingly important in companies. Through these techniques, it is possible to obtain useful information to improve the performance of the organization in the market and, in this way, conquer a significant competitive differential.
It is necessary to know the types of Big Data analysis to take advantage of this technology to the fullest.
From a set of data, the algorithms of this type of analysis manage to identify patterns and possible market trends. In this way, companies can use it to make forecasts.
It is an excellent option to study market conditions, seek consumption suggestions for your customers, identifying their profile, their needs, and desires.
The prescriptive model can identify what will be the consequences of the actions taken by the companies. It helps managers to anticipate possible reactions from their audience, which allows the strategies used to be better targeted.
In this way, companies can perform simulations and anticipate their actions to determine scenarios, which can significantly improve business results.
The descriptive analysis focuses on understanding the current situation of the company. It offers managers a complete and real-time overview of internal events and the organization’s position in the market.
Through it, it is possible to visualize the economic scenario in real-time. In this way, managers can make decisions based on correct and accurate information.
Finally, we can cite the diagnostic analysis, which prioritizes a mapping of the causes and consequences of the company’s actions concerning its current situation.
It is an excellent option when IT managers need to show the results of the organization’s performance and explain how it is in the present. By having an accurate diagnosis, company leaders can define corrective actions to solve specific issues and, thus, optimize business.
As you can see, Big Data analysis generates opportunities for organizations to grow and stand out in the market. For this reason, it is essential to know the existing types and direct them better in internal strategies to achieve better results.
Some benefits of Big data analysis in an organization include:
1. Improvement when discovering needs for the company
It implements technological enhancements for the company that enable the acquisition of data and allow to identify the needs and points of growth in the company.
2. Improvement in decision making
Another advantage is that data analysis can substantially improve decision making within a company by minimizing risks. Thus, some organizations are already optimizing their decisions by analyzing data from customers, employees, or even sensors incorporated in the products.
3. Evaluate the products and services of the company more efficiently
By analyzing data, they obtain valuable information that allows them to create new products or redesign existing ones.
4. Customer segmentation to customize actions
In this way, companies can guide their services and meet the needs of their consumers specifically. The customization of products and services is one of the trends that is currently treading.
5. Improvement of accessibility and fluidity of information within the company itself
Companies that digitize data and enable tools to facilitate the search for information will create a faster and more efficient work dynamic.
6. Competitive advantages
Competitive advantages in the large distribution: it allows updating, optimizing, and refining inventories based on real-time demand. Data mining or data extraction makes it possible to analyze customer behavior, set prices accordingly, or offer the right incentives to attract customers. It is possible to do it by digitizing items such as warehouses or cash registers.
7. Improvement of efficiency and costs
Big Data analysis can accelerate the speed with which a product is developed. It also allows you to share data quickly and perform product simulations. In some sectors, development deadlines have been reduced between 30% and 50%.
Harnil Oza is a CEO of Hyperlink InfoSystem, a mobile app development company based in USA & India having a team of best app developers who deliver best mobile solutions mainly on Android and iOS platform and also listed as one of the top app development companies by leading research platform. He regularly contributes his knowledge on the leading blogging sites.