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Data Analytics. Why data is one of the most valuable assets.

Data Analytics. Why data is one of the most valuable assets.

25 September 2022SHARE:
Written by:
Pedro Specter
Founder & Chairman

On a leave of absence acting as CTO to one of our partners!

We live in new periods of time. It is a new Era. The Economist has classified data as the most valuable asset in the world, even more than oil. It is though not a big "news", almost 100% of everyone is using data to harvest their flaws and gather new business opportunities, and without data, a PME cannot talk about scalability. Why is data the most valuable asset though?

Let's talk about Data Analytics!

Data analytics are the hypotheses that one takes from the analysis of the raw data that falls into a Datawarehouse. Our analysts are specialised in SQL language and combined with Statistical and Mathematical knowledge, - and some powerful algorithms we developed in house - they come up with some big insights and trends that help companies to reach their goals!

Data Analytics. Why data is one of the most valuable assets.

Data analytics, Data Warehouse, Data Layers, Business Intelligence, what is all that?

There is a lots of terminology in the field, however we make it simple for you to understand.

Imagine you have a retail store. You have clients, suppliers, products and other elements that produce raw data. In a Data-driven environment, this data is all collected and sent into a general database (or also known as data lake).

When falling into a data lake, the data is messy and raw. Here a data analyst or database administrator, (or in our case an AI algorithm) - refactors the raw data, and places it in a very organised database (also known as Datawarehouse) which is normal organised under a standardised model (STD90, EXO13, CDISC, etc...).

From the warehouse a data analyst / scientist is responsible to make suppositions around the data. These are called data analytics. Later these are again refactored and worked out in some specific algorithms. This process is known as the DIE (data intelligence extraction).

The latest process is to compare to the organisations problems and produce insights from the data. These can be of the type Descriptive - being the most common and presented under power BI or dashboards - Or, on the other side they can be predicative or prescriptive - and in this case they predict outcomes from business problems (liquidity flows, revenue trends, supplying crisis, etc…). And these go by the name of Business Intelligence (BI).

The value of data

Think about this base idea. Data is simply information that, when properly evaluated and tracked, can offer insights and solutions into your organisations current and potential problems. The ability to make confident business decisions, add value to the organization, and better inform product and service development is made possible by having clean, organized, and current data. Now the complex idea. When Data analytics become business intelligence, and combined with some smart people and comparing to the market trends, BI helps your organisation gaining an edge when compared to your competitors because you can easily identify patterns and predict outcomes of business decisions.

Some examples of value we provide to our partners:

  • Data Helps Meaningful Customer Engagement

  • Confident decisions based on data patterns identification

  • Adds value to the brand

  • Automates processes that would be hard to do manually

  • Helps R&D

  • Identifies problems and liabilities

As an example you can read this post about a case of one of our partners:

In our honest opinion, the true value of data is more than the above described topics. Data allows to understand the market and understand your company and where it is lacking. The proper data setup allows easier to go from 80km/h to 200km/h. And this is the true value, Data drives progress and innovation.

Business Intelligence makes Decisions

The ability of an organization to make wise decisions is directly impacted by the availability of thorough, high-quality data. Building confidence in organizational plans requires reliable data from statistically significant sample sizes, evaluated by qualified analytical experts. It enables firms to better understand the effects of their decisions on their business and can act as a baseline for what is already in place.

Furthermore, because data is logical and objective, it eliminates the subjective components from the decision-making process, enabling firms to foster a sense of confidence among all members of the company. As a result, businesses are better able to commit to a certain vision or strategy without being concerned that they made the incorrect choice.

Data Analytics. Why data is one of the most valuable assets.

Although Web 1.0 provided us with a fantastic means of connecting and communicating, we weren't really able to properly navigate through all the information at the time. Then followed Web 2.0, which saw the emergence of platform-based environments like Google, Facebook, and YouTube.

Then followed Web 2.0, which saw the emergence of platform-based environments like Google, Facebook, and YouTube. This made it easier for people to access and share data, but it offered those organizations an excessive amount of control. With the emergence of cryptocurrencies and non-fungible tokens, Web 3.0 is now becoming more widely accepted globally.

The end-user will have more authority and influence over the data generated as a result of his daily actions in ten years, whether it be on social media, via email, or in the metaverse. For a modern firm, knowing what data to collect and how to use this priceless resource might mean the difference between life and death. The most prosperous businesses can accurately portray a person by combining data from social media, emails, purchase history, and IoT devices. In order to influence their results, these businesses might then connect their business models and strategies with those of their customers. For instance, marketing teams are no longer required to distribute tens of thousands of mailers to conceivably indifferent consumers.

Data Predicts Behavior — And That Means More Revenue

To aid in predicting consumer behavior, businesses gather, store, and analyze consumer data in their own databases. Because of how accurate this predictive quality can be, a business may be able to forecast your needs before you do.

Think of the stale tale of Target being able to foretell when its female customers would become pregnant. Demanding to know why his teenage daughter was receiving mailers promoting diapers and other baby products, a furious father marched into his neighborhood Target store. He returned to the room a few weeks later to apologize after learning that his daughter was definitely expecting.

This story, which has almost a decade of existence, brilliantly exemplies why data is currently the most valuable resource for anyone. Twenty years ago, most businesses paid almost none or just a small attention into the numbers. They used data, for instance, to respond to inquiries about their profit margins, the impact of sales on inventory, and the costs of materials and shipping. However, businesses discovered along the road that, despite being essential, this data was not the key to unlock revenue or grow.

Understanding specific consumers was crucial, and thanks to advances in AI and processing capacity, that understanding is getting better and better. Today's data miners may change adverts and deliver them across devices to the precise individual who is most likely to make a buy, just like Target's incredible ability to determine when a lady was pregnant based on her purchases. Therefore, tailored advice practically guarantee purchases.

The secret to successful business outcomes is data

In today's commercial environment, data has emerged as the most valuable commodity by far. Understanding that data may not always be directly convertible into money is maybe one of the most crucial factors, but that doesn't make it any less valuable. A single sale today or an insight that would enable you to triple your sales income over the course of the following year—which would you choose? Future-fit foresight is the kind of data insight we should be searching for.

Given the volume of commerce conducted online, a solid data set of consumer preferences can provide a business the competitive edge it needs to anticipate what its customers will want before they do. Understanding and effectively utilising data is the key to achieving business outcomes in a world of competitors and when seconds count.

Don't invent the wheel, just ask for help

We are currently dealing with different projects that involve data warehouses models and ML algorithms and therefore having more partners belonging to our network and helping us developing our projects would take us to a more innovative step. Are you that partner? Perfect, contact us today!

Wanna know how we work? Send us a project today

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