Data is a key asset to any business wishing to join the 4.0 Industry. From searching for what your customers want, to knowing how your stock is changing or measuring the evolution of your main KPIs, data is indispensable to any organization wishing to survive. However, when data is wrongly interpreted it can hide vital information and blur decision-making. When the volume of data increases and it becomes unmanageable, Big Data Analytics culture becomes essential to help us make sense of not only what is happening, but mainly why.
Why is the market calling for Big Data Analytics?
To understand what Big Data Analytics is, first we need to understand the magnitude of Big Data. Let’s picture an organization in the food industry with international business, a portfolio of thousands of products and with a wide supply and logistics chain, including several stakeholders ranging from animal breeders to supermarket directors.
Inside this chain, each and every product produced, its costs, prices, distribution and selling means are mapped daily, generating millions of important data, which could be used to better understand the business and help decision-making.
All this information could be stored in sheets if the registry doesn’t go beyond 1 million lines ( PT-BR understand sheet limitations). As expected, this case exceeds this threshold and data ends up being collected and scattered among many sheets, sectors, processes, and so on. With that, some questions arise:
- How can we know which markets are thriving?
- Which are the market trends in different regions?
- Where are we short in stock and where is it excessive?
- Why am I losing market share?
- Which are the main bottlenecks of my supply chain?
- Which factors are more relevant in my profit margin by product, city, state, country?
Big Data Analytics is key to unravel these and many other questions.
Dimensions of Big Data Analytics
The 5Vs of Big Data
What Big Data Analytics does is deal with huge volumes of varied data with velocity and veracity, aiming to transform them into business value. These are the 5 Vs of Big Data and understanding them is fundamental to perceive where can we apply it to your business:
- Volume: Big data deals with huge amounts of data, turning them into information and then into knowledge. It is not uncommon here in our project to deal with millions of samples and thousands of factors. Drawing a parallel, picture a sheet with millions of rows and thousands of columns. It would be hard to make sense of something without Big Data Analytics, wouldn’t it?
- Variety: data acquisition can include multiple departments and sources inside an organization. We may need to collect data from clients, cross them with geo-populational data warehouses, government data, among others. All following current laws, of course! Discovering and grouping relevant data while keeping a foot on the ground is a big challenge that demands a mature data culture;
- Velocity: naturally, acquiring data is not enough. We need to devise effective strategies to transform it into knowledge as quickly as possible, before the competition takes the lead. In the race for information, interpret data promptly is power;
- Veracity: here at Aquarela we usually say that running models, chewing numbers and reaching results is the easy part. The difficulty lies in making sure that our analysis is leading us to coherent, real and high-value conclusions. In the end, a Big Data model is as good as the data we put into it. It is up to us to understand what makes sense and guarantee that the result mirrors reality;
- Value: it is in this V that lays the main result that drives Big Data Analytics: transforming data into value. After all, understanding what is going on and why things are happening is fundamental to support a more consistent and accurate decision-making.
Big Data Analytics increases business intelligence. While traditional analysis aims for explaining what is happening (in a very limited scope by the way), the use of Advanced Analytics is capable of finding the whys, what is hidden, or even feresights of what is going to happen. Big Data Analytics is a huge ally in developing new products, reducing cost and increasing efficiency, besides helping quick and safe decision-making.
Right data + right questions = right answers
Have you ever imagined opening a 6 billion cells sheet in Excel? Or, if the sheet opens, try and find behavior patterns that make sense and help you understand what is going on? Hard, isn’t it? The first challenge of Big Data Analytics is always to gather (or mine) data, a work that Data Engineers master. Data mining is vital (and usually a huge bottleneck) so that we can access data and groom it to analysis. Only the right data is able to offer us the right answers.
So now we are ready to start with the analysis, with data extracted, transformed, loaded (ETL), clean and coherent. At this point enters quantitative studies with mathematical models, or even Machine Learning models. That so we can use data so solve a wide range of problems. At this point, Data Scientists and Machine Learning Engineers enter in the search of solutions, which are often hidden. It’s the role of this team to create a scalable architecture, understand the client’s real problemas and fulfill the 5 Vs.
Big Data Analytics Maturity in Brazilian market
Clearly, reaching such maturity and proficiency in the 5Vs in a culture that is data-driven and with well-defined governance processes is not an easy task.
To investigate this fact, we performed a research study in 2018 that generated a report revealing the reality of data maturity in Brazilian organizations. In a scale from 1 to 5, participant companies reported their level of maturity.
We present the results below, indicating that the automation of intelligent behavior (level 5) is still low, while the great majority of them already have BI (business intelligence) systems implanted (level 3).
Big Data for Big Business
The projected revenue from business and Big Data Analysis is expected to reach 274.3 billion dollars by 2022 (IDC), with companies like Netflix saving up to 1 billion dollars per year by using Big Data (TechJury). To such organizations, a mature data culture is essential to keep growing and stay at the edge of the market. Organizations that use Big Data, either internalizing it or with partners, perceive a raise between 8 and 10% on profit (Entrepreneur), with benefits such as (Chicago Analytics Group):
- Innovation cycles 25% faster;
- Raise in 17% on efficiency and productivity;
- Research and Development 13% more efficient;
- 12% more differentiation on products and service development.
No wonder many companies are searching for improving their relationship with data. Unfortunately, data culture is still rare globally. Around 87% of the companies still have low maturity in matters of business intelligence and analytics (Gartner). The costs of such misinformation and low quality of data sum up to 3.1 trillion dollars by year only in the US economy (IBM).
The rapid growth and high complexity of Big Data Analytics make evident that the industry needs support. Organizations specialized in analytics can help propelling the digital transformation, especially for quick implementation of data solutions and artificial intelligence. Several organizations take high technological risks by trying to internalize such activities that are far away from their core business, while it would be much safer and more profitable to work together with companies specialized in Analytics.
Big Data Advanced Analytics culture at Aquarela
At Aquarela, our Big Data Advanced Analytics culture was developed and evolves constantly with focus on the Big Data Vs, good practices of data governance and in the enhancement of the technological stack that composes our VORTX platform.
We seek to deliver an experience of results based on analytics, capable of changing our clients culture. Our goal is to help the development of the industry and services that are experiencing an intense and needed process of digital transformation. To achieve this, we trust our clients and seek solutions with them, with all parts being equally essential for each project’s success. This goes beyond isolated data analysis, because collaborative evolution is an intense process guided by data, business experts, and information and technology specialists.
As results from our culture, we are able to upgrade the data maturity of our clients, providing dynamic and intelligent automated pricing systems, logistic actions recommenders, strategic maps of business intelligence integrated through AI, and industrial products optimizers also using AI. It is our big range of solutions that generate an expanded itelligence, which would not be possible without all data culture components acting synergically inside a clear vision on what artificial intelligence is.
Big Data Analytics is a very wide topic, and the 5Vs help us simplify this concept for managers to promote practical changes in the reality of organizations. Today, many companies present difficulties for reinventing themselves in this new digital economy, being for technical limitations in the intensive use of sheets, or by methodological and cultural limitations related to data.
In this article we undertook the task of showing you how the market is demanding more and more for analytics, which business points are more important in this matter, and the current data maturity levels of brazilian organizations. The main themes we recommend managers to keep an eye are:
- Data governance
- Development of a data-driven culture
- Optimization of distribution chains, logistics and commercial processes design
- Data privacy and ethics
- Data Analysis team training – We provide an e-book on analysis structuring (PT-BR)
Our interdisciplinary squads work daily with cutting edge technology to understand the challenges, find opportunities and solve your biggest problems. If in 4.0 Industry data is power, we thrive in empowering our clients to transform data into information, information into knowledge, and knowledge into strategic value to your businesses. It’s through the digital transformation that Aquarela expands the world’s intelligence.
Which Big Data Analytics challenges are you facing today? And what are you doing to overcome them? Leave us a comment!
Data Scientist and Service Designer at Aquarela, specialist in User-Centered Design and PhD student in Mechanical Engineering at UFSC with a focus on AI applied to creativity and innovation in organizations. Has experience as a consultant and speaker in AI, creativity, innovation and UX / Service Design.