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Home » Why Managing Data in the Cloud Helps Accelerate Business Decisions
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Why Managing Data in the Cloud Helps Accelerate Business Decisions

Pablo MorenoBy Pablo MorenoJuly 28, 2022Updated:August 1, 20224 Mins Read
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Managing Data in the Cloud
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We are immersed in a rapidly changing environment that multiplies challenges for decision-making. But what’s important to note is that the speed of change can slow down decision-making if the speed of data analysis is not made at the same pace. Luckily, we have the cloud!

Traditional Decision-Making

The traditional decision-making process involves many steps, from extracting data sitting in an application or database, to a decision-maker taking an action that will be replicated by others under the corporate hierarchy. In the middle of this ‘apparently simple’ end-to-end process, there are a good number of individuals gathering, staging, and cleaning data. Furthermore, the process involves aggregating data, formatting it into a report, and then sending out the report to someone who will add something else or combine that report with another report. The end result is a “Full View Report” that will be delivered to the top decision-maker.

Once the decision-maker takes an action based on the Full View Report, he transmits orders that will escalate down the whole hierarchy process. If these instructions are going down the whole hierarchy, some little ‘additions’ are enclosed — sometimes these additions are not so little.

Keeping in mind that it is a human process, the technology and infrastructure used to perform all these tasks have been based on on-premises databases and rely mostly on local computer work. This generates extra workloads on systems, as new files storing new information are generated — not to mention the many times the same information or data is saved and stored on different devices.

Accommodating Decision-Making for Changes

As you can guess, none of this is efficient, but it’s how many — if not most — organizations operate in many parts of the world. Resistance to change is inherent to human nature. We keep doing things as they are just because that’s how we best know them or because it has been done this way since before we can remember.

The whole process takes a lot of time, from the moment that any uncontrolled or new event occurs, it is captured with data, and any action is taken. Changes may be so fast that they have consequences even before the monitoring system sends alerts or we can even measure the impact or size in a report. Even with an efficient monitoring system and a procedure to retrain data models or make efficient and accurate analyses, the time necessary to remediate may be a critical threat, especially if retraining the data models on new data is not sufficient and a new analysis must be developed. During this time, the production systems misbehaving can cause large losses for the organization.

How to Navigate in a Highly Changing Environment?

As mentioned in the first paragraph, the cloud is the right infrastructure, as it allows for storing data that can change very quickly. It can also integrate many functional teams doing multiple things at a time. In addition, it eliminates the whole long process chain to consume and analyze data. The closer to the idea of ‘from data to decision’ instead of ‘from data to report to decision’ is effectively possible in a cloud environment.

There are as many organizations and company leaders hesitant to adopt the cloud as there are security concerns. Allow me to invite you to read my article How Secure is Data Stored in the Cloud? In any case, this change is only possible when business leaders and the whole workforce are ready to change the way they have been working — in other words, if they are all ready for a cultural change.

These days, technology change is very easy and affordable. Cultural change? Not so much.


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Pablo Moreno
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Business Data Scientist and Project Manager (Waterfall & Agile) with experience in Business Intelligence, Robotics Process Automation, Artificial Intelligence, Advanced Analytics and Machine Learning in multiple business fields, gained within global business environment over the last 20 years. University Professor of ML and AI, International speaker and Author. Active supporter of Open-Source software development. Looking to grow with the next challenge.

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