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How data-driven intelligence will help companies recover from the economic crisis

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

However, technology, especially the data industry, has taken a step forward to accelerate the search for solutions to build resilience. In the context of navigating these uncharted waters, data-driven intelligence will play a more important role in helping companies set sail for friendlier horizons.


Almost every sector of the economy has been hit hard by the global economic downturn, and companies everywhere are struggling to regain a foothold. What's the best way to go when faced with a fragile recovery?

If you stick to the general adage that every crisis is an opportunity, the data industry is in an ideal scenario to help companies make their comeback by not just fixing what's been lost, but developing new, improved solutions .

The search for a competitive advantage lies in striving for greater self-knowledge. Optimizing cost-effective resources and predicting how best to perform operations through data analytics and business intelligence is critical to the survival of the business.

This will drive many companies to invest, alone or with a trusted partner, to consolidate and modernize their data infrastructure and data intelligence dashboards to dispel numbing fog and make smarter, faster, and safer decisions.


The home office has proven to be an effective and popular mechanism for keeping business operations going without exposing employees, customers, and stakeholders to the risk of contagion.

The health emergency has actually accelerated a process that has already taken hold in many companies. A common, healing experience that has put an end to the widespread discussion about whether home office and productivity are in contradiction to one another.

However, the boom in teleworking will now require companies to invest further. Employees need to be able to stay connected, access and update company information, and collaborate with customers remotely.

Fortunately, this trend has fueled a remote office ecosystem like never before, while increasing pressure on sensitive areas such as data security and 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 just remote data storage, but also complex systems under IaaS, PaaS or SaaS models - the economic upswing has increased its importance.

According to Satya Nadella, Microsoft's CEO, before the COVID-19 hit, 54% of CIOs intended to invest in cloud solutions, while that percentage has risen to 89% in recent months. Companies are not only transforming the way they work, they are also adapting their business models to the paradigm shift.

The possibilities of the cloud were finally being considered, whether as a vault to protect data or as a trustworthy environment to provide flexible, scalable services to optimize resources in an increasingly digital world.

Database innovations - such as Microsoft's Azure Cosmos DB - pave the way to improved performance of data platforms and ensure that volume, speed and data diversity are not an obstacle.

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


All of this technology intensity delivered by new solutions leads to a complete redesign of the functional architecture of companies. Business models now contain algorithms to automate processes and extract valuable, usable information from data streams for the sake of competitiveness.

But we ask ourselves who should deal with this? Not every company has data analysts and scientists on hand. Many professionals in finance, human resources, or marketing are tasked with exploring new dimensions of business that involve the collection, refinement, and appropriate analysis of data.

It can be a challenge to acquire the necessary knowledge or even to recognize the potential of data intelligence. There are many obstacles in front of these experienced professionals who suddenly dive into a highly specialized, technical environment.

Power BI training can undoubtedly be an option to get to work as quickly as possible. But in an ever-evolving field, timely advice and troubleshooting from data experts can be worth its weight in gold. There's no point in gaining a lead only to lose it at the other end.


Smart cities have been a constant on the tech agenda for many years, but now new aspects have entered the debate. How can cities identify, prevent and respond to a major health crisis?

Take public transport as an example. Since the IoT is (hopefully soon) powered by 5G networks, cities can track citizen flows and adjust transit frequencies or even travel routes in real time. Finding and responding to large influxes of people who may pose a risk should also be an option. And that's just a drop in the bucket. Data intelligence could do wonders to optimize resources and make our cities a safer place for everyone.

However, intelligent control centers should be ready to deal with a massive, enormous amount of data - be it for later analysis or for immediate evaluation. At the same time, clear dashboards must show trained professionals the way, who can make decisions in the shortest possible time if the situation calls for it. Or maybe the weight of the decision lies in automated processes fed by machine learning and AI.

Smart cities aren't that far away, but they need smart data management.


Historically, automation occurs when there is a leap in technology that both improves and disrupts the traditional economy through waves of change.

Often associated with large, endless factories and imposing robots in the public perception, today's automation is somewhat different. Machine learning and artificial intelligence have democratized automation and made it accessible to companies regardless of size or activity.

Processes that used to take weeks, months or even years or required the commitment of many people can now be completed in next to no time. Solved by an “a la carte” algorithm and driven by automated processes that learn from experience.

For certain industries where data volumes can be overwhelming, artificial intelligence is proving to be the best choice. Take the financial markets, for example. ML & AI have proven invaluable in preventing, detecting, and blocking fraud or irregular transactions. Don't go that far: check out your Netflix, Amazon Prime, or HBO suggestions. They learn from what you watch and suggest new content.

New applications are in the news every day, like this latest and notable breakthrough from the University of Berkeley in biotechnology.


The use of 5G networks anticipates a networked world that is capable of developing or consolidating technologies that were previously considered inaccessible.

A 2017 Gartner study found that 57% of companies see IoT as the first application of 5G. However, the predictions indicated that the degree of adoption will be minimal by early 2020. Fortunately, widespread access to 5G networks is getting closer every day.

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

In short, you have the speed, but ... can you handle it?


Corporations' most important ally can suddenly become their worst enemy. Without an adequate, effective and constantly updated data security policy, companies can face paralysis, losses and discrediting.

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

With an increasing number of attack vectors and data theft - phishing, ransomware, malware, SQL injection, to name a few - the average cost of a data breach can be too high to recover.

Data security must be seen as insurance, peace of mind, and a guarantee that your company's best assets are in good hands and protected from cyber criminals. Even if it is you who makes a mistake, don't worry: your data can be recovered.

But this has to be planned in advance so that every step of the way is secured.


Business intelligence isn't just about walking around collecting endless streams of data, it's about turning them into a cohesive story. Careful review of the KPIs is mandatory, making sure that they are in context and provide useful insights for decision makers.

Data has to tell a story, from start to finish. Where do we start and why? Our dashboard needs to show a clear timetable for the variables we are tracking and isolate behavioral patterns that can add value to our sales funnel.

Sure, fancy dashboards with intelligent graphics and charts can help us move forward. However, the ability to customize and automate them may need to be acquired through training or mentoring. Decision makers and stakeholders need to envision business alternatives as clearly as possible and as quickly as possible.

Data analysis also constantly brings new trends with it - augmented analytics, embedded panels, mobile solutions. Whether by training in-house professionals or building a bespoke business intelligence model with a partner, companies need to be aware that data storytelling is a must.