Data Intelligence: According to IBM, we create 2.5 quintillion pieces of data every day. To put that in perspective, 90% of the data in the world today has been made in the last two years due to big companies joining the internet.
This means that we are facing a universe bombarded by information that circulates on the internet and in the cloud at speed millions of times greater than what we can assimilate through our human capacity. The crossing of so much data at once was possible thanks to the phenomenon of Big Data and the advent of other technologies that later made room for new forms of advanced programming with the use of Artificial Intelligence.
You must ask yourself where your company would enter in this context, and the answer is simple: if you haven’t entered yet, you need to rethink your management model and how you handle your data. Every company generates data, whether internal, external, structured or not. There are several sources and origins, such as the sales, logistics or accounting departments, customer records and even the service performed through multiple channels. Ignoring that this data can be used intelligently in its management means losing out to a competition already doing just that to survive the new times.
I use as an example and – if you allow me the analogy – the success story of Netflix. The company developed a disruptive business model that shook the outdated format of rental stores and even pay-tv by making movies and series available that could be watched at any time of the day and for a fixed monthly price. The exciting thing about this is that the company continues to reinvent itself and goes far beyond a virtual catalog today. The data intelligence applied to analyze the behavior of the platform’s users was used to guide content according to the identified preferences.
Access Standards
Access standards even helped the company know the type of content its customers wanted to consume and produce series and movies with all the necessary elements to impact and increase their audience positively. A proof of this is the company’s latest move with the release of the interactive fiction film Black Mirror: Bandersnatch, which allows the user to make choices that direct the course of the plot. And before you question what this has to do with your reality, think about how you could improve your products and services if you had a Business Intelligence team.
The case of Netflix is not far from the possibilities of any organization that, through data analysis, can understand the behavior of its customers and effectively guide its actions and strategies. Are you meeting your target audience’s expectations when creating e-commerce? Is your website user-friendly? All this and much more, you would have the possibility to explore with an adequate treatment of all the information that you already have in your business. The digital transformation journey is long, but the key to success is the same, start taking one step at a time.
Data Architecture
As it is still a maturing concept, it is believed that there are still several challenges with Big Data. However, its benefits are clear and no longer optional for companies that intend to survive the digital landscape. The range of applications is infinite, being a bass instrument for disruptive technologies, such as Artificial Intelligence and the Internet of Things (IoT).
This is because one technological evolution we are witnessing is the improvement of data analysis, using the Data Lake architecture, technology that takes BI to a new level by using an automated cloud. This type of data architecture seeks to give visibility to the mass of lost or poorly worked information and deliver insights that support strategic decisions.
An example is e-commerce. Everyday people buy products in virtual stores, but many of these companies are unable to extract, when interacting with customers, consistent information that can be used to their benefit.
Conclusion
With the data lake architecture, it is possible to deliver a more refined BI because we consolidate data from different sources in a single language in this construction.
The traditional BI approach delivers a macro database. When we apply Data Lake and a data scientist applies machine learning, the bots used for searches, for example, learn which results are of most interest to each manager, perform initial filtering and, with each search, further improve delivery of the appropriate information.
Also Read: Impacts Of An Integrated IT Solution On Business Results