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I am a highly motivated and organised professional with more than ten years of experience as a Database Specialist and Architect or designer.
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Tourism recovery mode

It’s wonderful to hear that LinkedIn Editors invited me! Pursuing a passion is an incredible thing. At this time, I have been invited by Mitchell Van Homrigh to contribute about how tech can solve tourism pain points. Below, you can find the points that woke up my interest.

 

Like many others, the tourism sector has been significantly impacted by the COVID-19 pandemic (it looks like that pharmaceutic ambition planned to destroy everything in its path, with the unique intention to get a couple of millions of dollars more in its revenue, another discussion for late). As we move towards recovery, technology could play a crucial role in reviving the industry. From my perspective, as a Data Management Engineer, I would like to highlight two things. Virtual Reality and Data Analytics.

  1. Virtual Reality (VR) Tours: The airline industry and people are recovering their health and “boom” stamina. For those planning tourism to any country or airport, VR tours can provide immersive experiences. The idea is to offer a VR tour of the destination airport, along with information on what to do before or after disembarking or boarding, such as where to go, what documentation is required, and emergency services information. When travelling to another country, it’s easy to feel lost because you don’t know how far the connection flight or migration/customs procedure is. VR tours can help passengers be more agile and reduce their time in the airport, improving the customer experience.

  1. Data Analytics: Tourism businesses can gain insight into customer behaviour and preferences by utilising data analytics to create more personalised experiences. This can lead to various benefits, such as predicting demand, improving pricing availability, and optimizing inventory for financial optimisation. In fact, a study showed that nine hotels experienced a 22% average increase in revenue after implementing pricing optimisation. Additionally, data analytics can inform funding decisions and shape business development based on detailed user preferences. By identifying potential customers at different stages of the trip planning process, analytics can help businesses target specific groups. Finally, data analytics can improve marketing campaign effectiveness by identifying the best channel to reach customers.

The innovative concept of virtual reality tours can potentially transform how we explore airports and destinations. In a world recovering from a pandemic, these immersive experiences offer a much-needed solution for travellers seeking a hassle-free and efficient journey. Imagine arriving in a new country and embarking on a virtual reality tour that guides you through customs procedures, connecting flights, and emergency services. This game-changing technology has the power to revolutionise the travel industry and create an even more satisfying experience for customers.

Regarding data, Analytics acts as a compass for tourist companies, guiding them in the right direction. By harnessing the power of data, businesses can gain valuable insights into customer behaviors and preferences, allowing them to create personalized experiences. Data analytics is the key ingredient for achieving operational efficiency and financial success, from predicting demand and optimizing pricing to shaping business strategies based on user preferences. This is a theoretical concept and a proven technique for boosting revenue and engaging consumers.

In summary, the COVID-19 outbreak had a major impact on the tourism industry, challenging its ability to adapt and recover. Looking ahead, it is clear that technology can play a critical role in supporting the industry. As a data management engineer, I believe virtual reality (VR) and data analytics are promising game changers. In this post-pandemic era, where the race to recovery is fierce, those who leverage technology wisely will survive and thrive, delivering the best service and experiences to passengers worldwide. The future of tourism is tech-infused, and it’s time to take that leap into a brighter, more innovative tomorrow.

 

AI and Data Management: A Powerful Partnership

Artificial intelligence (AI) is transforming every industry and every aspect of our lives. From healthcare to education, from entertainment to finance, AI is enabling new possibilities and creating new value. But AI is not a magic wand that can solve any problem without any effort. AI depends on data – lots of data – to learn, improve, and deliver accurate and reliable outcomes. And data needs management – effective management – to ensure its quality, accessibility, security, and integration.

What exactly does a Data Management Engineer do?

Data management is the process of collecting, organizing, storing, processing, analyzing, and sharing data in a way that supports business goals and complies with regulations. Data management involves various tasks such as data classification, cataloguing, quality control, security enforcement, and data integration. These tasks are often labour-intensive and error-prone when done manually or with traditional tools.

How AI can help to do our job more efficiently?

This is where AI can help. AI can automate and simplify tasks related to data management across discovery, integration, cleansing, governance, and mastering. AI can improve data understanding and identify privacy and quality anomalies. AI can also enhance data security by detecting threats and enforcing policies. AI can enable data integration by matching records across sources and resolving conflicts.
By using AI for data management, Database Specialist can benefit from:
  1. Improved productivity: AI can reduce the time and effort required for data management tasks by automating repetitive or complex operations.
  2. Increased accuracy: AI can improve the quality and consistency of data by identifying errors or inconsistencies and correcting them.
  3. Enhanced scalability: AI can handle large volumes of data from various sources without compromising performance or reliability.
  4. Greater agility: AI can adapt to changing business needs or regulatory requirements by learning from feedback or new information.
  5. Higher value: AI can unlock the potential of data by providing insights or recommendations that support decision-making or innovation.
Some examples of how AI can be useful for data management are:
  • Classification: AI can extract relevant information from documents, images, videos, or other media using natural language processing (NLP), computer vision (CV), or speech recognition techniques.
  • Cataloguing: AI can help locate data by indexing it based on metadata or content analysis using NLP or CV techniques.
  • Quality: AI can reduce errors in the data by validating it against rules or standards using NLP or machine learning (ML) techniques.
  • Security: AI can keep data safe from unauthorized access or misuse by applying encryption or masking techniques using ML techniques.
  • Integration: AI can help merge data from different sources by matching records based on similarity measures using ML techniques.
  • Data Cleansing: AI can automatically identify and correct errors in data by using machine learning algorithms. For example, AI can identify and remove duplicate data, identify outliers, and standardize data.
  • Data Governance: AI can help enforce data governance policies by identifying and flagging any inconsistencies or violations in the data. AI can also provide recommendations for policies based on the analysis of the data.
  • Data Discovery: AI can help discover hidden patterns and insights in large datasets that are difficult for humans to uncover. For example, AI can identify trends and correlations between different data sets and provide recommendations for further analysis.
  • Data Mastering: AI can help improve data accuracy and completeness by merging, standardizing, and de-duplicating data from different sources. This can help reduce data inconsistencies and improve data quality.
AI and data management are a powerful partnership that can enable organizations to leverage their most valuable asset – their data – in a more efficient and effective way. By combining human expertise with machine intelligence, organizations can achieve better outcomes faster while reducing costs and risks. If you want to learn more about how AI can help you with your data management challenges, please contact me, and we will be happy to assist you.
Regards;