Data-driven intelligence will play a crucial role for companies in 2021. The devastating effects of COVID-19 on the global economy have completely altered market forecasts. All over the world, companies have been forced to modify their business models and adapt to a new situation for the foreseeable future.

However, technology, particularly the data industry, has taken a step forward to accelerate searching for resilience-building solutions. In the context of navigating these unfamiliar waters, data-driven intelligence will play a more prominent role in helping companies set sail towards a more conventional horizon.


Almost every sector of the economy has been deeply affected by the global economic downturn, and companies everywhere struggle to regain their footing. What is the best path to take  when challenged with a tenuous restoration?

By adhering to the common saying that every crisis is an opportunity, the data industry is in an ideal scenario to support businesses in their comeback, by not only repairing what was lost, but setting up new, improved solutions.

The search for a competitive edge lies within the pursuit of greater self-knowledge. Optimizing cost-effective resources and predicting how best to conduct operations through data analytics and business intelligence is vital for business survival.

This will lead many companies to invest in consolidating and modernizing their data infrastructure and data intelligence dashboards, either by themselves or hand-in-hand with a trusted partner, dissipating mind-numbing fogs and making smarter, faster, confident decisions.


Remote working has revealed itself as an effective and popular mechanism to maintain business ventures without exposing employees, clients, and stakeholders to contagion risks.

The health emergency has actually sped up a process that was already taking root in many companies. A shared, healing experience that has terminated the widespread discussion on whether home office and productivity were at odds .

The rise of remote working, though, will now require further investments from companies. Employees must remain connected, able to access and update corporate information and collaborate remotely with clients.

Fortunately, this trend has fueled like never before an ecosystem of remote office solutions, while at the same time putting more pressure on delicate areas like data safety, as well as disaster prevention and recovery in a remote and distributed work scenario. A professional approach must be taken to optimize, maintain, and protect these shared workspaces and tools.


Although cloud computing has been around for years — not only remote data storage, but also complex systems under IaaS, PaaS or SaaS models — the bump in the economy’s way has heightened its importance.

According to Satya Nadella, CEO of Microsoft, before COVID-19 hit, 54% of CIOs intended to invest in cloud solutions, while the percentage has risen to 89% in the most recent months. Companies are not just transforming the way they operate but mutating their business models to adapt them to the paradigm shift.

The cloud’s possibilities have finally been envisioned, be it as a safe deposit for guarding data, or as a trusted environment to deliver flexible, scalable services, optimizing resources in an increasingly digital world.

Database innovation — like Microsoft’s Azure Cosmos DB — paves the way towards the improved performance of data platforms, ensuring volume, velocity, and data variety are not an obstacle.

Are you ready to migrate your databases to the cloud? If so, make sure you have a strong partner to work with you designing and deploying an efficient data migration process.


All this tech intensity delivered by new solutions is completely remodeling the functional architecture of businesses. Business models now incorporate algorithms to automate processes and extract valuable, actionable information from data flows, for the sake of competitiveness.

But let us ask, who should be looking at that? Not every company has data analysts and scientists at hand. Many professionals in finance, human resources, or marketing, have been tasked to deal with new business dimensions involving the gathering, refining and adequate analysis of data.

Acquiring the necessary knowledge, or to even realize the potential of data intelligence can be challenging. Many barriers stand in front of these seasoned professionals, abruptly submerged into a highly specialized, technical environment.

Power BI training can be an option to hit the ground running swiftly, no doubt. But, in an ever-evolving field, data professionals’ timely counsel and troubleshooting may bear its weight in gold. There’s no point in gaining an edge only to lose it through the opposite end.


Smart cities have been a constant in the tech agenda for many years, but now is when new features have entered the debate. How can cities detect, prevent, and react to a large-scale health crisis?

Take public transport as an example. With the IoT powered (hopefully soon) by 5G networks, cities can keep track of citizen flows and adjust transit frequencies, or even itineraries, in real-time. Detecting large influxes of people that can pose a risk and react accordingly should also be a possibility. And that is just a drop in the ocean. Data intelligence could work miracles to optimize resources and make our cities a safer place for all.

However, intelligent control centers should be ready to deal with a massive, enormous volume of data — whether for later analysis or for immediate evaluation. Simultaneously, clear dashboards must show the way to trained professionals, ready to make decisions in no time when the situation calls for it. Or maybe, the weight of the decision falls to automated processes fed  by machine learning and AI.

Smart cities are not so far away, but they need intelligent data management.


Historically, automation appears when a leap in technology takes place, enhancing and at the same time somehow disrupting traditional economics through waves of change.

Often associated in the public mind with large, endless factories and imposing robots, today’s automation is a tad different. Machine learning and artificial intelligence have democratized automation, making it accessible to companies regardless of size or activity.

Processes that previously could last weeks, months, or even years, or require many people’s input, are now finished in the blink of an eye. Solved through an algorithm “a la carte” and powered by automated processes that learn from experience.

For certain industries where the volume of data may be overwhelming, artificial intelligence is revealed as the best choice. Take, for example, the financial markets. ML & AI have proved invaluable to prevent, detect and block fraud or irregular transactions.  Do not go that far: check out your Netflix, Amazon Prime, or HBO suggestions. They learn from what you watch and suggest new content.

New applications can be found daily in the news, like this recent and remarkable breakthrough from the University of Berkeley in bioengineering.


The deployment of 5G networks anticipates a hyperconnected world capable of developing or consolidating previously considered unattainable technologies . 

A Gartner study from 2017 advanced that 57% of companies saw the IoT as the first application of 5G. Predictions indicated, however, that the level of deployment would be minimal by early 2020. Fortunately, widespread access to 5G networks becomes closer every-day.

But 5G involves higher volumes of data, at greater speed, without interruptions. Behind the scenes, data platforms need to be able to handle this and escalate the allocation of resources as needed. Optimal maintenance, monitoring, and troubleshooting should always be close at hand to avoid disaster scenarios.

In a nutshell: you have the speed, but… can you handle it?


The prime ally of companies can suddenly become their worst enemy. Without an adequate, effective, and continuously updated data security policy, companies may face paralysis, losses, and discredit.

Data security cannot be a minor issue in a world where cyber-crime is on the rise. Data breaches have increased 64% from 2014, and global spending on cybersecurity will total $133.7 billion in 2022, according to Gartner.

With an increasing number of attack methods and data theft — phishing, ransomware, malware, SQL injection, you name it — the average cost of a data breach can be too high to recover from.

Data safety must be seen as insurance, peace of mind, and a guarantee that your company’s best asset is in good hands and protected from cybercriminals. Even if it is you who makes a mistake, do not worry: your data can be retrieved.

But that must be planned in advance, so every step of the road is safeguarded.


Business intelligence is not just about running around collecting endless data streams but turning them into a coherent story. A careful examination of KPIs is mandatory, while ensuring they are in context and contain actionable insights for decision-makers.

Data must tell a story, from beginning to end. Where are we starting from, and why? Our dashboard must clearly show a timeline for the variables we follow and isolate behavioral patterns that can add value to our sales funnel.

Sure, fancy dashboards with smart graphs and charts can help us work our way forward. However, the skill to customize and automate them may need to be acquired by training or mentorship. Decision-makers and stakeholders need to envision business alternatives as clear as daylight, as quickly as possible.

Data analytics are also bringing in new trends continuously — augmented analytics, embedded panels, mobile solutions. Whether through training in-house professionals or building a custom business intelligence model with a partner, companies must be aware that data storytelling is a must.