Today’s business world is changing at a dizzying pace and the decisions we make must be more agile and accurate than ever. In this context, data analysis is essential to facilitate the path towards smarter decisions that bring greater value to the business.

To do this effectively, it is necessary to have a good data analysis strategy to identify needs, opportunities and suitable use cases.

In this article we take you on a journey through the 5 key steps that will allow you to get the most value from your data.

1. Let’s start with the basics: define what you want to achieve through your data.

Our journey begins with what is fundamental to any strategy: defining objectives. Although it may seem obvious, the first thing to understand is that data analysis is not just about crunching numbers and statistics.

This means that before implementing more advanced techniques and technologies, it is important to understand your organization’s needs, objectives and challenges. That’s what will guide you to collect, process and leverage your data in a meaningful, business-serving way.

In addition, well-defined objectives allow you to measure progress and evaluate the impact of data analytics on business objectives. Without solid objectives, data analytics will lack direction and focus, wasting resources and time.

2. Let’s continue in order: Where will you store your data?

Once you have your objectives defined, the next key step is to decide where to store, collect and organize your data in the cloud.

There are data repositories that you can choose according to your different purposes and needs. For example, if you need to keep as much data as possible without losing information, you can opt for a data lake, also known as a Data Lake, which allows you to store large amounts of raw data and to which you can resort whenever you want to explore new or unknown data.

In terms of organization and data collection, another option is to build a data warehouse, also known as Data Warehouse, which will allow you to have at your fingertips a structured repository, that is, where all the important data is already organized and ready for use.

In addition, with a modern Data Warehouse, you can perform advanced analytics techniques such as descriptive, diagnostic, predictive and prescriptive analytics, from which you can extract valuable knowledge and insights from your data.

We recommend this digital event with DEMO
to discover how to have a modern Data Warehouse, connect your business data, transform it and start making smarter decisions.
Access the event on demand!

It is time to analyze!

Once you have established a solid foundation for your data, the next step in your journey is to start analyzing it for insights in order to make smarter decisions based on data rather than intuition.

To this end, another key step in getting the most value out of your data is the effective combination of different analytics approaches and scenarios, such as data science and real-time analytics.

While data science provides the depth and insight needed to make informed strategic decisions, real-time analytics gives you the agility to react quickly in an ever-changing world.

However, the combination of data science and real-time analytics is a dynamic process that requires a solid technological infrastructure as well as teams specialized in both disciplines.

4. Technology, the icing on the cake

In this journey towards maximizing the value of your data, it is essential to select the right tools and solutions to make the data analysis process as efficient as possible.

Ambitious companies have already started to opt for fully integrated cloud solutions that allow them to store, process and analyze their data easily and securely.

Microsoft Fabric, Microsoft’s new unified cloud data analytics solution, combines technologies such as Data Factory, Synapse Analytics, Power BI, Real-Time Analytics and Synapse Data Science, so organizations can store, integrate and analyze their data all from one place.

In this way, you will be able to establish a single source of reliable and unified data that will allow you to democratize access to your data and reduce the time and effort of your teams to obtain valuable knowledge.

5. Wait, without a specialized team, everything will be more difficult…

The last point, but not the least, is the fundamental role of a specialized team.

However, many companies do not have the resources to implement, manage and master these types of cloud solutions, a complex task considering the large number of different technologies and products that are often disconnected from each other.

That is why many companies rely on a specialist partner with the necessary know-how and experience to not only advise and assist them in the implementation of technologies, but also to accompany them along the way.

As Top Cloud Partner of Microsoft, Softeng accompany you on the road to maximize the real value of your data. Want to know more? Our team will be happy to talk to you.

Data analytics has become a priority for many companies. However, there is one particular feature that makes it difficult to manage: the amount of data is constantly growing. In this article we unlock the key data management challenges so you can overcome them and manage them without losing control.

Companies have large volumes of information, often redundant and disconnected. As has been demonstrated time and again, data alone is not enough. The key lies in the ability to integrate and analyze this data effectively to unlock valuable insights to support strategic decision making.

But how do we analyze our data if it is constantly evolving? Effective data management in the cloud has become a competitive advantage. Those companies that manage, store, organize and secure their data in the cloud without losing control will be more prepared than ever to make better decisions that make a difference.

However, the large amount of information, and the variety of disconnected services and solutions, have brought with them challenges that affect most companies. These challenges, far from being insurmountable obstacles, can be successfully addressed for enterprises to take full advantage of the benefits of cloud data management.

3 main challenges of data management in the cloud

1. Scarce resources

If we imagine the cloud as the home of our data, having the right team and tools to build it and take care of it is essential.

The implementation and management of cloud data platforms usually requires the participation of teams of engineers and developers with high technological expertise and training. However, this can be costly and sometimes almost inaccessible for many organizations.

Lack of data governance

Once we have built our house, it is also important to secure it so as not to put at risk what we have inside. Data governance refers to sound policies, standards and procedures for managing, organizing and protecting data stored in the cloud. Without them, companies can be hit with common cyber-attacks and privacy issues.

3. Search for a single, reliable source

We now have our house ready and secured. But it would be of no use if what we have inside is in disarray.

In the cloud era, companies often have data from a variety of sources, in different formats and often from different vendors. Having a single, reliable source to unify this data, identify it, analyze it and give it a strategic purpose can become a real challenge.

Addressing the challenges of data management in the cloud

As the evolution of data increases and the need for strategic decision making becomes increasingly important, many companies have begun to adopt cloud solutions that are secure, integrated and easy to implement.

The Microsoft cloud offers solutions such as Microsoft Fabric that enable companies to integrate, store, analyze and govern their data from a trusted, unified source.

However, due to a lack of resources and the priority of not compromising security, many digitally ambitious companies choose to rely on a partner to support them and help them maximize the potential of their data through efficient management and ensuring control along the way.

In Softeng, as Top Cloud Partner of Microsoft, our team of cloud experts can accompany you on this journey to maximize the management of your data. Contact us so we can move forward together on your business objectives.

Business strategy based on data and artificial intelligence is booming. Organizations have realized that the value of their data lies not only in the quantity, but also in the quality and how they use it to make smarter, more strategic decisions.

But, as with all emerging technologies, it is very difficult to adopt them without first having to do a lot of research to find what is really tangible and interesting behind the noise, while always maintaining our zero-trust cybersecurity posture in the face of new cyberthreats that are also emerging.

Specifically, Data and artificial intelligence technologies complement and enhance each other to improve processes, providing great added value to advance business objectives faster and more securely. Analyzing the environment, finding behavioral patterns, predicting consumption trends or optimizing processes are just some of the use cases where we can take advantage of its full potential. But where do we start if we want to maximize the value of the data? For the foundations. And for this, first of all, it is essential to have a modern data warehouse. And second, connecting business data and transforming it in a way that is fit for purpose.

Building a modern Data Warehouse

A Data Warehouse provides a centralized and structured repository where data from various sources, such as operational databases, enterprise applications and cloud systems, can be stored. This allows for a comprehensive and unified view of the data, facilitating analysis and accurate reporting.

Some organizations have their own Data Warehouse. Even so, many are still not taking advantage of the benefits of a modern cloud data warehouse, such as scalability, performance, availability, advanced analytics capabilities through AI and cost reduction to create much more flexible, faster and secure data repositories.

We recommend this digital event with DEMO to discover how to have a modern Data Warehouse, connect your business data, transform it and start making smarter decisions. Access the event on demand!

Connecting business data and transforming it appropriately

Once the Data Warehouse is configured, the next step is to connect the necessary business data and transform it in an appropriate way to ensure the quality of the data in the right format, under the principles of integrity, continuity and availability.

Once the data is available in the Data Warehouse and has been transformed, it is possible to start making smarter, evidence-based decisions. Data analysis can reveal patterns, trends and relationships that were not previously visible, allowing organizations to gain valuable insights for strategic decision making. In addition, it can also help identify opportunities for improvement, optimize operations, understand customer behavior and anticipate market trends.

In the current context, the ability to securely connect the organization’s data to ChatGPTThe new solution, following the best security and privacy practices, offers new opportunities to solve different business processes, allowing to take advantage of the knowledge and analytical capacity of the model to obtain information and quick answers about different aspects of the business.

We recommend this digital event with DEMO
to discover how to securely connect your organization’s data with ChatGPT to solve different business processes.
Access the on-demand event!

In conclusion, having a data-driven strategy and knowing how to maximize the potential of new technologies allows companies to unlock the full potential of data to make better decisions, solve problems more efficiently, and gain a competitive advantage.

Digital event:
Discover how to maximize the value of your data with advanced analytics and ChatGPT technologies.


Attend the on-demand event!

Artificial intelligence (AI) and Generative Pre-trained Transformer (GPT) technology have emerged as powerful tools capable of transforming the way companies operate and make strategic decisions. The adoption of these technologies to drive digital innovation will generate a very significant impact for those companies that are able to maximize their potential by creating next-generation business applications.

In this article, we explore the benefits of AI adoption with ChatGPT through 4 use cases, using the capabilities of Microsoft Azure Cognitive Services and Azure OpenAI Services:

1. Improve the user experience and reduce the workload of the Helpdesk team.

Business application:
Virtual customer service assistant.

How: By leveraging the potential of Azure Cognitive Services’ Language Understanding Conversational AI Service (LUIS), the virtual assistant is able to interact naturally and provide faster and more accurate responses to user queries and even understand the intent of the query.

2. Improve productivity and personal organization

Business application:
Personalized virtual assistant for task management.

How:
Using Language Understanding (LUIS) and Text Analytics, the assistant can understand user requests and questions, track tasks, send reminders and provide personalized recommendations.

3. Increase engagement and drive sales

Business application:
Virtual assistant for personalized recommendations.

How: ChatGPT can be combined with Azure Cognitive Services’ Personalizer service to develop a virtual assistant that provides personalized recommendations to users based on data history and behavioral patterns, among others.

4. Increase the efficiency of business processes with quick access to information.

Business application:
Virtual assistant for internal corporate information search.

How:
Leveraging Azure Cognitive Search to perform semantic searches by indexing all types of documents, files and internal databases, along with ChatGPT offering a conversational interface to process user queries, with the goal of finding specific information faster, more accurately and securely.

As artificial intelligence and GPT technology continue to evolve, more use cases will emerge whose application in business processes will become an important part of the business process. must in digitally ambitious companies, due to its great usefulness and efficiency, in order to continue advancing their business objectives in an increasingly competitive world.

Discover in this digital event
how to build a modern Data Warehouse and how to connect ChatGPT with your business data in a secure way, through different use cases and practical examples.

Access the event on demand!

Process automation helps us to simplify and standardize processes, making them more efficient and much more robust. In addition, thanks to technology, each of the automated processes provides us with a lot of valuable information to better understand what we do and how we work.

Therefore, automation is not something isolated, but must be treated as part of a gear that works together with data analysis, the creation of solutions and business applications, etc. But what is the next level?

The sophistication of automation to reinvent processes that learn, anticipate and act efficiently

When we take process automation to the next level, we no longer just talk about automating repetitive tasks, but go further by combining automation itself with advanced technologies such as artificial intelligence, machine learning or RPA (Robotic Process Automation), among others, to design, automate, supervise, measure and analyze each process in order to maximize its potential. We are talking about hyperautomation.

As Gartner predicted, hyperautomation has been a growing strategic trend during 2021, and will continue to be so for the next few years, mainly due to the search for more efficient ways to manage business processes in an increasingly changing and competitive environment. . Thus, it is not surprising that in those companies that are already in an advanced digitization process and understand the cloud and innovation as levers for progress, the hyper-automation of processes is one of their priorities.

Microsoft Power Platform tools help us transform and enrich our data – which would otherwise have to be mechanically and repetitively fed by a person – in order to achieve operational excellence, with greater optimization, quality and cost savings.

You want to know more?

Do not miss the digital event that we will celebrate on Thursday, May 5, in which you will be able to see the creation of a digital business process enriched with artificial intelligence.

sign up now

Want to know which of your customers you have more risk of losing or what product you have more chances to sell?

Now, with your historical data and predictive technology Microsoft “Azure Machine Learning”, you can get answers to these and other questions and so advance you take appropriate action.

Get valuable insight from your data

Companies have increasing amounts of data (Big Data) at their disposal and with the right tools and techniques, it is possible to extract valuable information, not only to understand the present, but also to predict the future.

Until recently, this type of analysis could only be done through complex software, powerful computers and scientific / mathematical. Now with machine learning platform Microsoft in the cloud, you will be able to recognize trends or patterns to predict future behavior, without having great knowledge.

Machine Learning offers different types of analysis to get the information:

• What happens? (Descriptive analysis)
• Why does this happen? (Analysis diagnosis)
• What will happen in the future? (Predictive analysis)
• What is the best action to take? (Prescriptive analysis)

Through these analyzes you will be able to:

• Extracting information to understand and define a situation or problem.
• Predict scenarios and situations.
• Make smart decisions and assessing the likely consequences.
• Implement improvements and automate processes.

In short, you’ll get results from high value to help you make good decisions.

Machine Learning is everywhere
Although we do not realize the predictive power applications are part of our daily life, such as: Mail spam filter, the results pages of search engines, suggestions contact on social networks and many more applications and services that live with us for some time and help us to be more productive.

If you want to know more about Azure Machine Learning, you can view this video:

Now the machine learning techniques are available to everyone and Softeng as specialist partners solutions in the cloud Microsoft, we help you get the most out of Azure.

Want to know more about how we can help?

If I want to