{"id":10528,"date":"2021-10-28T16:06:20","date_gmt":"2021-10-28T16:06:20","guid":{"rendered":"https:\/\/assist.com.co\/?p=10528"},"modified":"2026-02-25T15:18:17","modified_gmt":"2026-02-25T15:18:17","slug":"las-empresas-y-los-datos-en-que-se-relacionan","status":"publish","type":"post","link":"https:\/\/assist.com.co\/en\/2021\/10\/28\/las-empresas-y-los-datos-en-que-se-relacionan\/","title":{"rendered":"Companies and data\u2026 How are they related?"},"content":{"rendered":"
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<\/strong>During the end of last year and the beginning of this, we have found that organizations are more determined than ever to tackle transformation processes. Some in an accelerated way, forced by circumstances, another fruit of<\/span> a well thought out plan and path. In either case, the word \"Data\" is found at some point.
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Introducing myself to this area of technology and presenting ourselves to various challenges of reference companies in Colombia, I have discovered several data that serve to put us in context:<\/span><\/p>\n<\/blockquote>\n<\/div>\n

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\u00b7 Utility: According to a Forrester study of December 2020, companies currently use on average only 27% of their data to make decisions. In other words, we underuse 73% of our data, having not \u201cData Lakes\u201d but \u201cData Cemeteries\u201d.
\n\u00b7 Accessibility: An employee today, says the same source, spends between 2 and 3 hours a day looking for information. The data is not accessible, it takes time to access it and therefore make decisions late.
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<\/strong>\u00b7 Data growth: Without a doubt, the growth of the data generated by our companies and their ecosystem exceeds what our mind can understand. It is exponential, rather than linear. At this point, a 580% growth of the data is expected in 5 years. In other words, if we continue to treat the data as today, we will no longer use 73%, but much more, approaching 90%.
\n\u00b7 Ecosystem: The data of a company has much more value in the context of an ecosystem. An ecosystem that is increasingly open to sharing data in favor of having better services, insights and a better customer experience. Not connecting with said ecosystem would make the company lose a lot of value. In any, step by step.
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\u00b7 Customers: according to the Huffington Post, 67% of customers mention bad experiences as a reason for abandonment, but only 1 in 26 dissatisfied customers complain. And they don't complain because they don't have channels with good experience to do it. AI components can enable not only more channels but better experience. And there is no Artificial Intelligence without data to learn from.<\/span><\/p>\n<\/blockquote>\n<\/div>\n

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In the above context, undoubtedly, a company must understand its data as capital to build competitive differences. But ... how to do it?<\/span><\/strong><\/p>\n

Point 0 is definitely asking different business questions: Is the journey that I think my clients have, is it supported by data? What are the important variables to make our processes efficient? Productivity of my employees?<\/span><\/strong><\/p>\n<\/div><\/div><\/div><\/div>

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Then, there are a series of activities that make up the ladder towards the democratization of data, proposed by IBM:<\/strong>
\u00b7 Collect: Facilitate-simplify the collection and access to data.
\u00b7 Organize: Create the basis for business analytics.
\u00b7 Analyze: Build and scale Artificial Intelligence with confidence and transparency.
Infuse: Deliver the promise of Artificial Intelligence throughout your business.

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These four steps imply rethinking the following aspects of the information technology framework in your company.<\/strong><\/p>\n<\/blockquote>\n<\/div>\n

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<\/strong>\u00b7 Information architecture of the company. Without a correct architecture, there is no possibility of scaling Artificial Intelligence.
\n\u00b7 Definition of a Data Governance Policy: Who can access what information and the reliability of this data is the basis for a data strategy. The different technology enablers are based on certain management frameworks.
\n\u00b7 Technology Roadmap: The involvement of components in each echelon should be prioritized, even with open components. In the step of infusing and analyzing, one could think of the OPENDATA HUB project, an open project that can add value.
\n\u00b7 Talent in architecture and development of data models: Today they are scarce, therefore companies should think about developing this talent, together with the roadmap that is built.<\/span><\/p>\n<\/blockquote>\n<\/div>\n

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Starting the path to a data-centric company is not an option. The when and how can be discussed. This can be aligned with the budget and the roadmap, where there must be different early victories that leverage advancement and knowledge in the company. The budget is still a problem, but much less than before. Many technology components work as software as a service, and some even have free licenses to get you started. In addition to that, there are open components that can be used very well, some even already supported by companies such as IBM through business support.<\/span><\/strong><\/p>\n<\/div><\/div><\/div><\/div>

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So do not wait any longer and define a path. While you read this article surely the data in your company grew and therefore the opportunity to make better decisions.<\/strong><\/span><\/p>\n<\/div><\/div><\/div><\/div>

SOURCE<\/span><\/h3>\n

* Forrester Source:\u00a0<\/span>https:\/\/go.forrester.com\/blogs\/hadoop-is-datas-darling-for-a-reason\/<\/a><\/p>\n

* IBM \/ Dec 10, 2020 \/ \u00a9 2020 IBM Corporation: Una empresa de datos, anal\u00edtica e inteligencia artificial<\/p>\n

*\u00a0<\/span>https:\/\/www.huffpost.com\/entry\/customer-service-can-kill-your-customers-experience_b_5929f8dde4b07d848fdc0455<\/a><\/p>\n

* OpenDataHub:\u00a0<\/span>https:\/\/opendatahub.io\/<\/a><\/p>\n

*\u00a0<\/span>https:\/\/assist.com.co\/analitica-inteligencia-artificial\/<\/a><\/p>\n

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