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Technology

The importance of QA

Software Quality, necessary and important before the advancement of technology.

Technology advances and it has no plans on stopping. Every day we see its new and innovative proposals. This is not something that surprises us but rather it is already part of our daily lives, and therefore it is not an option to leave technology out of our daily living, controlling and managing it yes, but not isolating ourselves from it.

For this reason, if something becomes a necessity, it is important that we trust it and that is where the quality of software comes to give technology a hand so that in addition to meeting important life needs, it can maintain its level of confidence between its users.

For some years now, software quality has been working hard on creating standards, principles, techniques, and methods to guarantee that the technology is safe and reliable as well as optimal and of a high level.

The importance of software testing not only seeks that the product can meet its specifications, which used to be the main goal. Now, the paradigm has evolved and additionally, of verifying if the product meets the specifications, software quality takes an important leap and provides mechanisms that seek to prevent possible failures during any process of the software life cycle.

Last but not less important, this practice seeks that the product satisfies the client’s needs in a proactive and captivating way.

It’s about creating a universal culture of this important area of the software world, technology with a high level of quality and constantly increasing, guaranteeing a better experience with it, saving significant costs, time and protecting the reputation of large software production companies as well as emerging ones.

The quality of the software is everyone’s responsibility, it is true that there are specialized teams for this practice, but when we are all joining forces, time and knowledge; we have a common goal and in a certain way we all reach the point of becoming good testers who take care and guarantee that each of the processes complies with the highest possible quality until reaching its delivery points or final project closure.

It is not enough to just trust technology, but it is possible to guarantee and demonstrate that it is trusted through software quality.

 

Anuard Michelen Ramirez | Software QA Team Leader at Utreee | Cofounder of IDCAS

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Technology

What is Predictive Analytics, its Benefits and Challenges?

What is Predictive Analytics, its Benefits and Challenges?

Predictive analytics is a form of advanced analytics that is used to make predictions about uncertain future events. Predictive analytics leverages many data mining, analytical and predictive modeling techniques are used to bring together the information technology, management, and business process to make future predictions. Patterns from historical and transactional data are analyzed, and then the future opportunities and risks are identified that help decision-makers make an optimal decision.

Benefits of Predictive Analytics for Businesses:

Understand Customer Needs:

By leveraging smart analytics, businesses can get an in-depth and precise picture of who their customers are and what they really want. 

Predictive analytics can be used to reduce the number of business risks by getting insights into things like the success of new products, getting an idea of businesses they are dealing with, or assessing the demand of something in the future to identify new opportunities.

 

For instance, you may be launching a new beauty product such as a face mask, by using predictive analytics, you will know how much demand for a similar product like a charcoal mask had in the past and how much demand you can expect for your product in the future.

Mitigate Risk:

If you have a lower risk, then obviously your cost would be lower as well because you will not face failures in the future that lead to financial losses. Furthermore, by analyzing future trends, you will be able to take better steps towards working on an optimal approach and reduce costs.

For instance, if you are buying an asset, you can leverage predictive analytics to determine its maintenance needs beforehand so that you can properly service it and reduce costs that may incur if it stops working.

Cost Reduction:

If you have a lower risk then obviously your cost would be lower as well because you will not face failures in the future that lead to financial losses. Furthermore, by analyzing future trends, you will be able to take better steps towards working on an optimal approach and reduce costs.

For instance if you are buying an asset, you can leverage predictive analytics to determine its maintenance needs beforehand so that you can properly service it and reduce costs that may incur if it stops working.

Challenges with Predictive Analytics:

  • Having Expertise:Having Expertise: This is one of the primary concerns for businesses because predictive analytics solutions are usually designed for people with a deep understanding of statistical modeling, Python, and R like Data Scientists. This limits teams without knowledge of these things to properly leverage predictive analytics solutions.
  • Adoption: Predictive analytics solutions are typically standalone tools which means businesses will have to discard the use of their primary business applications to get this solution. If a company does that and its team doesn’t learn how to use predictive analytics solutions, it can be a big problem.
  • No Actionable Insights: Predictive analytics solutions are usually limited to just providing data about future trends. They do not provide insights to end-users that can help them take action. So, for this, end users have to switch to another tool and may interrupt their workflow.

Final Words:

These are just some of the benefits and challenges that companies face when dealing with predictive analytics solutions. Keep in mind that there are some predictive analytic tools out there that have overcome these challenges that could provide your businesses with an all-in-one solution.

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Technology

Big Data – How Business are implementing it?

Big Data – How Business are implementing it?

Big Data has been around for some time now, but many people are still confused about what it is. Honestly, it’s a concept that is still growing and being reconsidered, but in simple words, big data is the reflection of things happening in our world. The more things happen, and changes occur, the more data is collected and due to its huge size traditional means of data mining, and data management, these are not applied to its processing. Instead, massive scale technological tools are used to process it and use it for future decisions. For instance, analyzing tons of medical records and images to seek patterns that can spot diseases early so medicines can be made beforehand. This article will talk about how businesses are using big data for their growth.

How Business Are Leveraging Big Data in Puerto Rico and all over the world?

There are various ways through which businesses are using big data to predict future trends, make strategies accordingly and get an edge over their competitors. Below are a few ways businesses are using it.

Boosting Customer Acquisition and Retention:

Big data allows businesses to observe various patterns and trends related to their customers. With the right data mining strategies, businesses can get all or most of the relevant data from their customers and then use it to trigger loyalty. If a business has a proper consumer data analytics mechanism in place, it will be able to derive critical behavioral insights. And once it understands those insights, it will be able to deliver what the customers want from you which will help you acquire new customers and retain the current ones.

Better Risk Management:

Risk management is the key that saves a business from any damage by mitigating it before it even occurs. If we talk about the financial markets, banks and big investment companies use big data to forecast future trends and the risk of the market going against them. By using various big data analyzers and trend indicators, they decide the point where they have to sell or buy currencies/stocks to mitigate any risk.

Helps With Product Development and Innovation:

Another big advantage of big data is that it helps companies bring innovation to their products. By getting data on what can precisely fit the needs of their customers through various sources like for example data mining companies, entrepreneurs develop just the product based on further analysis and logical reasoning. This is exactly how Amazon Fresh and Whole Foods work. They utilize their data-driven logistics to understand how suppliers interact with grocers and how customers buy their groceries and then bring something new whenever possible.

Final Words:

Data is rapidly changing our world and how we live in it. If big data is capable of doing all of this now, imagine what it could do in the coming years when there are more advanced tools and techniques to process and analyze big data. Therefore, businesses that view data as their strategic asset will be the only ones that will thrive in the future. UTreee is implementing Big Data solutions for many local companies in the US, Puerto Rico, and the Dominican Republic assuring great success for their clients.

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Technology

The latest trends en BI

THE LATEST TRENDS IN BI

Data is vitally important to any business, regardless of size. With increasing volumes of data available, companies are starting to implement business intelligence (BI) solutions that will enable them to make informed decisions based on data. To be successful in a highly competitive area, companies must not only prioritize implementing a modern BI approach but also educate their workforce to be analytics experts. For organizations to retain their competitive advantage, organizations must recognize the roles, technologies, and business strategies that will enable them to improve their approach to BI. UTreee is one of the companies that specialize in creating and implementing Business Intelligence solutions in the United States, Puerto Rico, and the Dominican.

AI (Artificial Intelligence) and Machine Learning

Many organizations are still unsure what artificial intelligence (AI) can do for their business. While technology is improving rapidly, machine learning (ML) is becoming an indispensable feature for analysts, providing help and improving efficiency. 

An analyst can have more time available to think about how their analysis will impact the business and plan the next steps by automating simple, time-consuming tasks. This will also help your analysts stay on top of your data flow. Without having to stop and analyze their numbers, analysts can dig deeper. While the potential of AA to assist analysts cannot be denied, it is critical to understand that it should only be implemented when the results are clearly defined. Although some may be concerned about being replaced, ML will help analysts be more accurate and have more impact on the business.

NLP (Natural Language Processing)

It is anticipated that 50% of analytical queries will be generated through speech, natural language processing (NLP), or search by 2020. NLP will allow people to ask more subtle questions about the data and get specific answers that could lead to better insights and decisions.

Crowdsourcing data governance

BI has been disrupted by self-service analytics and the same is happening with governance. As self-service analytics capabilities increase, new information and valuable insights lead to innovative new ways of implementing governance. The wisdom of the crowd in government is used both to get the right data to the right person and to prevent the wrong person from accessing the data.

The modern governance model will use BI and analytics strategies where data engineers and IT departments select and prepare reliable data sources. This will allow end-users to use self-service to explore safe and reliable data.

Multicloud

It is estimated that 70% of companies will use a multi-cloud strategy by 2019. As companies become increasingly cautious about being locked into a single legacy solution, implementing and evaluating multi-cloud environments can reveal who provides the best support and performance for specific situations. Although this approach is flexible, it increases costs by dividing workloads between vendors and expecting internal developers to learn multiple platforms. With the rise in multi cloud adoption, companies must evaluate their strategy by measuring internal usage, adoption, implementation costs, and workload demands for different platforms.

The location of things

The location of things is a subset of IoT that includes all the devices that are used to detect and communicate geographic positions. Having access to this data allows users to take it into account when evaluating usage and activity patterns. This technology is also used to track people and assets. It can provide a more personalized experiences when interacting with mobile devices such as badges and smartwatches. With data analysis, location-based information can be viewed as an input versus output from results. Analysts can incorporate this information if the data is available to understand what is happening, where is it happening, and what should they expect.

Conclusion

All companies have data available, but how they use it will ultimately determine the value derived from it. Although the BI techniques discussed in this article are currently top trends and will help organizations increase their competitive advantage, there are many more that can help organizations reach their full potential. No matter where you are – the US, Dominican Republic, Puerto Rico, or anywhere else – data is critical to your business, and business intelligence can give you the technology advantage you need to make your data count. At UTreee, we specialize in creating a BI solution that work just for you.