What are the main difficulties SMEs will have when they want to start working with data?

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In my last article, we talked about how SMEs can also use data to grow their business and access new opportunities in the market. However, if we analyse the situation from a broader perspective, we will quickly realise that multiple factors prevent these businesses from taking advantage of the data they have.

These factors can be understood as entry barriers, which difficult these companies from competing on equal terms in a technologically mature market. We will explore the main 6 entry barriers that any business that wants to start working with their data will face. …

Discover how small and medium-sized businesses can also extract value from data

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Since I started writing on Medium, I have focused on the value that data have. In articles like “How much is your firm losing because of poor data quality”, “What is Business Analytics?”, or “This is how the data that will change your business is processed” we have explored data from different perspectives and how these are important in order to gain competitive advantage in the market. However, you may have the feeling that driving your business with data to allow your business to grow healthy and compete in the market is just something that large corporations with long budgets…

What customer-centricity approach is and how customer analytics can help

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In this week’s article, we are going to talk about a slightly different topic than what we have been dealing with in the previous weeks. We will stop talking about “data in the cloud” for now to talk about how data can help us to better understand our customers.
You will agree with me on the fact that, regardless of the sector in which you work, customers are essential, since they are the ones who finally buy products or services and allow business to be profitable and grow healthy. However, although we are aware of the importance of the client, you…

4 considerations to keep in mind when working in the cloud

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Welcome to a new article on the data in the cloud series. If you have missed any of the previous articles, I recommend you to do a quick read and catch up since in this article we will continue talking about the cloud, and it is highly recommended to be in context. In the first article of the cloud series, we talked about the advantages and disadvantages of the cloud, and how it can help your business. In the second, we explained what the different cloud service models are and what you are responsible for in each of them.


Understanding the cloud models and the shared responsibility with the service provider

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In this second article on the data in the cloud series, we’re going to explore one interesting concept that has emerged in the cloud: the shared responsibility model. When thinking about moving to the cloud, you should first understand the different cloud options and how this will affect your organization. Depending on the deployment model you choose, you will have a higher or lower responsibility.

If you missed up the first post in the data in the cloud series, I recommend you to read first the article How the cloud will help (or not) your business, since we’re going to…

Understanding the cloud main advantages and disadvantages

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In this article, we are going to change the context slightly. In the last articles, we have been talking about data management, the importance of data quality, and business analytics. This time, I am very excited to announce to you that we are going to explore, over the next few weeks, a current trend that will affect all companies in the decade in which we find ourselves: the cloud. I know that the topic cloud is very broad since it has a lot of concepts so we’ll focus on data in the cloud.

I think by now, we have all…

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From questions to answers, an explanation of the complete data analysis process

In my last article, What is Business Analytics? An understandable explanation of what analytics is and what types there are, we defined that word that appears everywhere today: analytics. Also, we have identified 5 different types, which has helped us better understand how we can find answers to different question types by exploring our data. However, extracting value from data is not a single-step process. To extract the right insights from data, we have to go through a process that allows our firms to extract the diamond from the rock.

An understandable explanation of what analytics is and what types there are

An understandable explanation of what analytics is and what types there are
An understandable explanation of what analytics is and what types there are
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With the arrival of Big Data, everything related to data has grown exponentially, mainly due to three of its 5 V’s: speed, variety and volume. The amount of data daily generated has been growing exponentially and that’s the reason why the tools and techniques used to analyse data have had to evolve and adapt to these new changes while new ways of exploiting data are being created.

Big Data is an enabler which allows you to use data in a different, more complete way, and which, together with artificial intelligence, allows you to extract greater value from the data. Companies…

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Deleting a Python version on your Mac can be a real headache. Many solutions on the Internet do not work, so in this story, I am going to share with you the steps that I have followed to completely eliminate the version of Python that I had installed on my Mac.

Note.- It is recommended that you have a certain fluency with the handling of the terminal.

In my case, I am removing Python 3.9. If you have another version, you will have to replace literal “3.9” of the commands with the corresponding version.

Step 1: Remove the Python framework

sudo rm -rf /Library/Frameworks/Python.framework/Versions/3.9

Step 2: Remove the Python applications

sudo rm…

Understanding poor data quality and where it comes from

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In my previous article, I talked about how poor data quality can severely harm a company, increasing its cost structure and, therefore, reducing its potential revenues. In addition to costs, there are other problems indirectly associated with poor data quality, such as mistrust generated by customers, loss of business opportunities, fraud, or poor decision-making.

However, in most cases, poor data quality does not occur due to specific problems or errors, but to repeated habits, actions, and processes over time that cause small errors, the cost of which may seem negligible but it ends up becoming a high issue for the…

Samuel Fraga Mateos

Restorative, entrepreneur, strategic, and futurist. Engineer with a technological background who love business, finance, and strategy.

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