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If You Wait, You’re Late. Stop Thinking You Need to Do Your Data Lake First Before you Leverage AI 

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By Ryan McQueen

Learn how to skip the data lake and employ AI agents that can access, understand, and use your data to deliver solutions. 

Introduction 

Data is the fuel of the modern business world. It can help you understand your customers, optimize your processes, and innovate your products. But data alone is not enough. You need to be able to use your data to drive the future execution of your business. That means you need to act. 

However, acting with data is not as easy as it sounds. Many businesses face challenges in collecting, storing, processing, and analyzing their data. They spend a lot of time and resources on building data infrastructures, such as data lakes, that are supposed to make their data ready for use. But data lakes often create more problems than they solve. They are complex, costly, and cumbersome. They do not guarantee that the data is consistent, reliable, or usable. They do not enable the data to be accessed and used by the people or the models that need it. They do not deliver the solutions that the business needs. 

In this blog post, we will show you how to skip the data lake and employ AI agents that can access, understand, and use your data to deliver solutions. We will explain why data lakes are not the answer to your data problems, and how AI agents can help you overcome them. We will also introduce you to DeepSee, a set of applications that allow you to deploy AI agents quickly and easily, without waiting for endless data projects and IT budgets. With DeepSee, you can start using your data to drive your business now, and deliver the experience that your customers and business expect in the new AI-First Generation. 

Why data lakes are not the answer 

Data lakes are a popular approach to data management that involves storing all your data, regardless of its source, format, or structure, in a single repository. The idea is that by having all your data in one place, you can make it easier to access, analyze, and use it for various purposes. 

However, data lakes have many drawbacks that limit their usefulness and effectiveness. Some of the main drawbacks are: 

  • Data lakes are hard to build and maintain. They require a lot of technical expertise, infrastructure, and governance. They often involve moving data from various sources and systems, which can cause delays, errors, and inconsistencies. They also require constant monitoring, updating, and cleaning to ensure the data quality and security. 
  • Data lakes are hard to use and understand. They do not provide any context, meaning, or structure to the data. They do not tell you what the data is, where it came from, how it was collected, or what it can be used for. They do not help you find the relevant data for your specific needs or questions. They do not enable you to query, explore, or visualize the data easily. They do not support the collaboration and communication between different users and stakeholders. 
  • Data lakes are hard to leverage and optimize. They do not guarantee that the data is ready for use by the people or the models that need it. They do not ensure that the data is consistent, reliable, or accurate. They do not enable the data to be processed, analyzed, or transformed promptly and efficiently. They do not deliver the insights, answers, or solutions that the business needs. 

In short, data lakes are not the answer to your data problems. They are a data side-hustle that distracts you from your core business. They make you work for your data, instead of making your data work for you. 

How AI agents can help you use your data to drive your business 

AI agents are software programs that can perform tasks or actions on behalf of a user or a system. They can interact with data, systems, and other agents, using natural language, voice, or other modalities. They can learn from data, feedback, and experience, and improve their performance over time. They can act autonomously, proactively, or collaboratively, depending on the situation and the goal. 

AI agents can help you use your data to drive your business in many ways. Some of the main ways are: 

  • AI agents can access and understand your data, wherever it is. They do not need to move or store your data in a data lake. They can access your data from its original sources and systems, using the appropriate protocols and permissions. They can understand the context, meaning, and structure of your data, using natural language processing, computer vision, and other techniques. They can extract the valuable terms, entities, and relationships from your data, using named entity recognition, relation extraction, and other methods. 
  • AI agents can use your data to deliver solutions, whatever they are. They do not need to wait for the data to be ready for use. They can use your data to generate answers, insights, or actions, using machine learning, deep learning, and other algorithms. They can use your data to either train or fine-tune a model, using supervised, unsupervised, or reinforcement learning. They can use your data to deliver solutions that are relevant, reliable, and accurate, using validation, reconciliation, and optimization techniques. 
  • AI agents can help you improve your business performance, however you measure it. They do not need to rely on the data that is available. They can help you collect, generate, or augment your data, using data collection, data generation, or data augmentation techniques. They can help you improve your data quality, security, or governance, using data cleaning, data encryption, or data auditing techniques. They can help you improve your business outcomes, such as customer satisfaction, operational efficiency, or revenue growth, using data-driven decision making, data-driven automation, or data-driven innovation techniques. 

In short, AI agents are the answer to your data problems. They are a data solution that supports your core business. They make your data work for you, instead of making you work for your data. 

How DeepSee can help you deploy AI agents quickly and easily 

DeepSee is a set of applications that allow you to deploy AI agents quickly and easily, without waiting for endless data projects and IT budgets. DeepSee is designed for businesses that need to improve their regulated process performance, such as insurance, banking, or healthcare. DeepSee helps you overcome the challenges of data complexity, data quality, and data compliance, and enables you to use your data to drive your business. 

DeepSee offers many benefits that make it a unique and powerful tool set. Some of the main benefits are: 

  • DeepSee is fast to configure and deploy. You do not need to have any technical or coding skills to use DeepSee. You can configure and deploy AI agents using a simple and intuitive user interface. You can use the existing templates and workflows or create your own custom ones. You can deploy AI agents in minutes, not months. 
  • DeepSee is easy to use and understand. You do not need to have any data or AI expertise to use DeepSee. You can use and understand AI agents using natural language, voice, or other modalities. You can interact with AI agents using chat, email, or other channels. You can monitor and control AI agents using dashboards, reports, or alerts. 
  • DeepSee is flexible and scalable. You do not need to have any fixed or predefined data or AI requirements to use DeepSee. You can use DeepSee for any data or AI problem, solution, or goal. You can use DeepSee for any data or AI task, action, or function. You can use DeepSee for any data or AI source, format, or structure. You can use DeepSee for any data or AI volume, velocity, or variety. 

In short, DeepSee is the tool set that you need to deploy AI agents quickly and easily. DeepSee is designed for your business needs, your data needs, and your AI needs. DeepSee helps you use your data to drive your business now, and deliver the experience that your customers and business expect in the new AI-First Generation. 

Conclusion 

Data is the fuel of the modern business world. But data alone is not enough. You need to be able to use your data to drive the future execution of your business. That means you need to act. 

However, acting with data is not as easy as it sounds. Many businesses face challenges in collecting, storing, processing, and analyzing their data. They spend a lot of time and resources on building data infrastructures, such as data lakes, that are supposed to make their data ready for use. But data lakes often create more problems than they solve. They are complex, costly, and cumbersome. They do not guarantee that the data is consistent, reliable, or usable. They do not enable the data to be accessed and used by the people or the models that need it. They do not deliver the solutions that the business needs. 

In this blog post, we showed you how to skip the data lake and employ AI agents that can access, understand, and use your data to deliver solutions. We explained why data lakes are not the answer to your data problems, and how AI agents can help you overcome them. We also introduced you to DeepSee, a tool set that allows you to deploy AI agents quickly and easily, without waiting for endless data projects and IT budgets. With DeepSee, you can start using your data to drive your business now and deliver the experience that your customers and business expect in the new AI-First Generation. 

If you want to learn more about DeepSee, or see how it can help you use your data to drive your business, please visit our website or contact us for a demo. We would love to hear from you and show you how DeepSee can make your data work for you.