Blog | London Consulting Group

Artificial intelligence in data analysis

Written by London Consulting Group | Jul 10, 2024 2:30:16 PM

Companies are enrolled in the era of digital transformation. Therefore, it is important to stay ahead of the curve and opt for the use of artificial intelligence in data analysis, as it is the current trend that seeks to raise the potential of any business.

Real-time analytics, automation and advanced data visualization are some of the elements considered to improve the internal processes of an industry. This approach provides an effective strategic value for decision making in all areas of responsibility.

In this article we will learn about artificial intelligence applied to data analysis, its importance and how a business solution can minimize the impact of betting on new technologies.

Artificial intelligence in data analytics

Data analysis is a task that usually takes a long time and requires a qualified team to minimize the mistakes that can be made. However, with the advent of artificial intelligence, this process has undergone major changes, making the use of a tool almost mandatory if productivity is to be maximized.

AI is capable of analyzing unstructured data through tools such as natural language processing (NLP), speech analytic transcription, among others. Automation has thus become a key element for the success of businesses facing information analysis challenges.

The whole focus of artificial intelligence is on facilitating the entire process involved in reviewing data, such as predicting sales, detecting suspicious behavior, automating certain processes or activities within a company to make better decisions and discover opportunities for improvement.

What is artificial intelligence in data analysis for?

Artificial intelligence in data analysis has different functions that can enrich the approach within a company, among which we can highlight the following.

Data collection

One of the first functions of AI is the ability to collect information automatically and on a large scale, as it is possible to extract different information from different sources such as social networks, online surveys, logs or websites.

Thanks to the power of artificial intelligence, the time it saves is very noticeable, and there is a lower demand for resources as opposed to manual methods.

An example of this is Power BI, an analytics tool from Microsoft focused on providing interactive visualizations and data-related business intelligence capabilities, allowing users to create their own reports.

Text analytics

Among the data it can collect, AI makes it possible to analyze large volumes of text to extract information about users' opinions or attitudes when they are searching for valuable content at any stage of the buyer journey.

Thanks to this, it is possible to better understand people's behavior, patterns, preferences and demographics, making it possible to focus on a better targeting strategy to respond to the specific needs of a sector.

Identify market segments

The use of AI in data analysis allows to identify market segments taking into account behavioral patterns, user preferences, age range, search intention and country or population to which they belong.

Trend prediction

Thanks to the information gathered from different sources, it is possible to forecast future market behavior, allowing businesses to adopt strategies based on more accurate data and respond strongly to new public needs.

Price optimization

In the industry it is important to maximize the use of capital, so by taking into account factors such as demand, competition and profit margins. AI data analytics makes it possible to make a company's profitability and financial returns easier.

Automated reporting

Once all the data has been collected, it is possible to automate reporting, giving the people responsible a clearer and more effective view of the results.

Strategic decision making is based on this point, which is why the potential of AI in data analysis must be exploited to the full.

Benefits of artificial intelligence in data analysis

The information-oriented AI functions have benefits that help any type of industry. A first strong point is the cost reduction associated with the professionals needed for efficient data analytics, since it is a tool that, if used well, can save time and resources.

Likewise, other advantages of implementing an AI in this process are the following.

  • Risk management: helps improve the efficiency of risk models and enables the development of more intelligent and optimal strategies.
  • Innovation: AI data analytics tools enable big data to drive updates to existing products and create new ones.
  • Chain supply: thanks to AI it is possible to apply data-driven insights to solve any type of challenge in the supply chain.
  • Engagement: facilitates the process to better understand the public and be able to respond to the specific needs of a sector.   
  • Competitive advantage: AI gives a company an edge over the competition, as digital times demand always being at the forefront.

A competitive solution for the use of AI in data analytics

In relation to the problem of implementing the use of artificial intelligence for data analytics, there is a lack of knowledge about the future of this technology and the most effective ways to use it.

In this sense, a strategic partner can provide business solutions to respond to the challenges. London Consulting Group provides Analytics, Data and BI, offering an option to streamline the entire process we have outlined.

The business solution is mainly oriented to the exhaustive analysis of the processes to determine the training required with the collaborators to make intelligent use of the new tools.

The objective is to develop dashboards and customized reports that facilitate the precise measurement of all the information that is being collected, which thanks to AI is much more agile and accurate.

London Consulting Group's solution has three fundamental pillars that mark a before and after in data analysis:

1. Analytics, Data & BI

The methodology is based on the assumption that not only the experts in the field of data, such as data engineers, data scientists, analysts and developers, have access and knowledge of the analysis after the BI process, but that the entire team is aware of it and can be understood to streamline the processes by areas.

2. Data quality

The goal of using new tools is to achieve a data-driven organization, and for the whole building to be sound, you need data that is reliable, complete and has in it the ability to drive your analysis and actions to get it.

To do this, the right processes and technology must be in place to get the data you expect, and this is where AI plays an important role in streamlining and minimizing errors due to manual cases.

3. Business intelligence and reporting

Finally, the whole process leads to time savings for the entire team to search for information and make fully informed business decisions, while also providing clear KPIs to know how each of the business tasks is developing in real-time.

Thanks to this, it is possible to implement improvement strategies and achieve success in a much simpler way.

Conclusion

The use of artificial intelligence for data analysis is beginning to revolutionize the way in which information can be obtained from different media, such as competitors, products and consumers.

To maintain a competitive advantage, it is important to implement technology that seeks to gather data in an accurate and much more agile way. Solutions like those offered by London Consulting Group aim to maximize the full potential of a workforce.

At the end of the day, AI enables the automation of manual tasks while providing profound insights to help industries make better decisions.

Start the transition to the future with Analytics, Data and BI, optimizing processes with world-class data analytics technology.