Data is the oil of the future and data analytics is the seismic.

Data analytics enables organizations to collect and analyze all their data to identify patterns and generate insights to support decision making at both the operational and strategic levels.

Classic reporting strategies to support decision making are becoming obsolete. They have been complemented and enriched with more robust models generated from internal and external data that allow modeling the company’s reality in a more accurate way.

Those responsible for a process must have an analytical attitude based on data to solve organizational problems by generating models, both descriptive and predictive, that allow companies to strengthen their competitive advantages.

Taking advantage of internal and external information on user traits and habits, market trends, resource utilization, loss and inventory levels, among others, generates large information patterns that can help to establish optimization actions, take advantage of opportunities or reduce costs.

Modeling business reality

As a starting point, in data analysis you can count on a descriptive statistic of the main business variables that can be very useful to find opportunities or reduce costs.

Supporting decision making

The large amount of data, or Big Data, can help generate user-friendly reports that allow process managers or senior management to automate decision making.

Evolution of data analytics processes and models

What stage are you currently at?

At the beginning, great value was placed on statistics. Then the models can be more complex and automate decisions.

Some questions to answer:

– What is going on? Business Analysis

– Why is this happening? Diagnostics

– What is going to happen? Predictions

– How do you make it happen? Optimization

Evolution of data analytics

Data analytics solution components

Integrating team efforts with different responsibilities, or working hand in hand with a specialized it consultancy such as Ecoeffy.

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Visualize business data and KPIs

Business Intelligence-based business analysis, based on strategies, key objectives and performance indicators, allows focusing efforts on results.

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Automation

From repetitive and complex tasks, such as report preparation and data consolidation. This is one of the main benefits. However, it is not the only way to automate operational tasks with AI.

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Machine Learning

- Classification
- Forecast
- Data Scientist

Recorded Benefits of Data Analytics to Date

According to a study by Forester (2019) Customers who have transformed their businesses with purpose have gained:

Average ROI
%
increased customer satisfaction
%
faster in statistics calculation
%
cost reduction
%

Safety is no less important

Given the sensitivity of the information, the way in which this information is protected and accessed is of particular relevance.

Access control

To objects

To ranks

A columns

Authentication

In the SQL

Active directory

Multifactor authentication.

Network security

virtual networks

Firewall

Another great advantage of data analytics is that it fosters innovation.

AI is everywhere

The use of AI and data analytics in business is justified by Forbesstatistics  McKinsey and Oberlo

more global investment in AI
x
of organizations have adopted AI in one area of business
%
64% of business owners believe it will improve customer relationships.
%
expect AI to drive sales growth.
%

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