<p>We're happy to announce&nbsp;<strong>DBAQL&nbsp;</strong>(Database Agnostic Query Language), a query language created by InsightBase, that can be used to query multiple databases (and data sources).</p>
<p>&nbsp;</p>
<p>DBAQL is a huge improvement for our platform in many ways, as well as an improvement for our customers and how they interact with their data sources, and here's how it will impact everyone using InsightBase:</p>
<ol>
<li><strong>Get better and more accurate results</strong>. Since all the AI systems are not 100% accurate, using DBAQL to calculate the results means that the results will be more accurate.</li>
<li><strong>Build your own queries</strong>. If you don't like the AI answer, you can just build the query manually, to answer your question. We will still use some AI magic though, for some other minor things.</li>
<li>Soon, you will be able to run queries using DBAQL through our API and create Widgets dynamically. It will allow you to build powerful widgets for your customer-facing apps, without being afraid of what the AI system will reply.</li>
<li>Soon, you will also be able to edit the query that was used by the AI, in order to improve it or make any fixes, if the AI system is not very accurate.</li>
</ol>
<p>This is just one of the powerful updates that we're going to roll out soon.</p>
<p>Note: DBAQL is in Beta, so please use it carefully and contact us if you have any problems using it.</p>

Introducing Database Agnostic Query Language

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Introducing DBAQL

<p><a class="sc-e9215096-0 bGjXSk activePath" href="https://www.rawpixel.com/image/2803897" target="_blank" rel="noopener noreferrer">Image</a>&nbsp;by&nbsp;<a class="sc-e9215096-0 bGjXSk activePath" href="https://www.rawpixel.com/" target="_blank" rel="noopener noreferrer">rawpixel.com</a></p>
<p>&nbsp;</p>
<p><strong>Business Intelligence&nbsp;</strong>is the technical infrastructure that collects, stores, and analyzes the data created as the result of a company activity.</p>
<p>It is a wide term that implies multiple aspects, like data mining, data analysis, predictive analysis, etc.</p>
<p>&nbsp;</p>
<h2>Business Intelligence Benefits</h2>
<p>All the companies are using business intelligence one way or another, even if they're not aware of it. Even the most simple and small companies generate some data, and usually store it somewhere, which means that they're involved in business intelligence. However, not all companies are taking full advantage of it and using it to their benefit.</p>
<p>Having the right business processes is important as it allows the company to make data-driven decisions and achieve its goals faster and very often cheaper.</p>
<p>&nbsp;</p>
<h2>Business Intelligence Use Cases</h2>
<p>Business Intelligence has a wide range of use cases and it can help companies in a lot of different ways. We'll cover just a few ways of using business intelligence.</p>
<h3>Improving Sales</h3>
<p>By collecting all the sales data into a single place, and analyzing it, organizations can dive deeper into their sales processes, find out which products sell best, or what type of customers are more likely to purchase their products, as well as see the regions that are more likely to generate sales</p>
<h3>Unlock Marketing Data</h3>
<p>By tracking the marketing efforts, like traffic, visitors, and purchases across different campaigns, companies can focus their efforts on the marketing channels that work best in order to maximize their marketing returns.</p>
<h3>Customer Discovery</h3>
<p>Making sure that the customer is always happy is key to a company's success. Business intelligence can help a company learn more about its customers and improve their satisfaction. By analyzing their customer behavior, as well as how the customers use the company products or simply analyzing their most successful customers, companies can fix their processes or improve their products to deliver a better experience.</p>
<h3>Other Use Cases</h3>
<p>Other use cases include, but are not limited to:</p>
<ol>
<li>Supply Chain Optimization</li>
<li>Financial Performance and Reporting</li>
<li>Operational Efficiency</li>
<li>Market and Competitive Analysis</li>
<li>Risk Management and Compliance</li>
<li>Human Resources and Workforce Analysis</li>
<li>Predictive Analytics</li>
</ol>
<p>&nbsp;</p>

Learn about Business Intelligence and how it can help your company

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Business Intelligence

What is Business Intelligence?

<h2>New integration: Airtable!</h2>
<p>We're happy to announce that our Airtable Integration is finally here!</p>
<p>We had a lot of requests for Airtable integration, and now it's finally ready.</p>
<p>You can "chat" with your Airtable now. Whether it's asking simple questions, or generating charts from your data, we've got you covered.</p>
<h2>How to connect to Airtable</h2>
<p>In order to connect to Airtable, you have to go to your Organization Settings (top left corner), then go to the Integrations tab, and click the <strong>Enable</strong> button on the Airtable Card. You will be redirected to Airtable and prompted to select the bases that you want to give access to. Once you do that, your Airtable will be connected to your InsightBase organization, and you'll be able to create new Data Sources from your integrations.</p>
<h2>Querying your Airtable base</h2>
<p>There's no substantial difference between querying Airtable and a regular database like MySQL in InsightBase. All you have to do is ask a question. What's important though is to make your question clear so that our system will understand it better and return accurate results.</p>
<p>All the other features like monitoring are going to work with Airtable as well.</p>
<p>&nbsp;</p>
<p>Stay tuned for updates, because we're working on a lot of interesting things.</p>
<p>&nbsp;</p>

New integration available: AIrtable. Easily analyze your Airtable data with InsightBaseAI

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New integration: Airtable!

<p>In the age of AI, it's becoming more and more essential to make sure that everything you do aligns with AI because it will be much easier to implement and use AI to grow and improve your business.</p>
<p>Your data is important for your business and it can be a powerful force, giving you insights about your current business situation, as well as predictions on how to improve it.</p>
<p>One critical aspect we found out at InsightBase about the data, is the data architecture. It's essential to have an AI-ready data architecture in place because it makes analyzing the data much easier.</p>
<p>Even though the current AI systems are already powerful enough to analyze your data, it's even better if you architect your data in a way that will make it way easier for AI systems to explore it. Let's dive into some specific examples and actionable steps that you could perform to improve this aspect of your business.</p>
<p>This guide is database agnostic, and we won't dive deep into data architecture concepts that apply to any database.</p>
<p>&nbsp;</p>
<h3>Naming</h3>
<p>I can say that this is one of the biggest problems for AI systems, and getting this right can offer you huge advantages when analyzing your data with AI. Having the right names for your tables and fields will make it way easier for the AI, and anyone else working with your data. Here are some things that you could do to improve this aspect of your data architecture:</p>
<ol>
<li>Avoid shortening the names. For instance, someone could shorten&nbsp;<strong>prospect_lifetime_value&nbsp;</strong>to&nbsp;<strong>pl_value</strong> .&nbsp;</li>
<li>Remove redundancy. For instance, if you have an <strong>orders&nbsp;</strong>table and a <strong>status</strong> field, make sure to name it&nbsp;<strong>status</strong>, instead of&nbsp;<strong>order_status</strong>. This will also help you save some spacing</li>
</ol>
<h3>&nbsp;</h3>
<h3>Setting the right field types</h3>
<p>When creating a table field, make sure that you user the right type. When an AI system is inspecting your database structure, it makes decisions based on your database schema, and having the right field types would help the AI systems a lot.</p>
<p>Here's what you can do:</p>
<ol>
<li>Use&nbsp;<strong>boolean</strong> instead of an integer with <strong>0&nbsp;</strong>(for false), and&nbsp;<strong>1&nbsp;</strong>for true values. When generating SQL code, AI systems will usually generate a code that implies that your field is either True or False, and not "0" and "1".</li>
<li>Avoid using integers instead of "enums". For instance, if you have a status field that can be either: "pending", "received", or "shipped", make sure to use a string with those specific values, instead of using a number status, like "1" for "pending", "2" for "received", and "3" for "shipped". I know that someone will say that this can save storage space and make indexing faster, but indexing can also make database writes slower, and space is not an issue in our days.</li>
</ol>
<h3>&nbsp;</h3>
<h3>Keep the important fields at the top level</h3>
<p>Most databases allow you to have sorted fields in one way or another. Make sure that you keep the important fields at the top level and avoid nesting them. It will be easier for the AI systems to generate the right code to analyze your data.</p>
<p>&nbsp;</p>
<h3>Conclusion</h3>
<p>If you follow the above steps, you can see 2x, and even 10x improvements in data analysis, and this will help not only the AI systems but also will make the software development process easier, it will make it easier for everyone that's analyzing your data to query, understand and analyze it.</p>
<p>&nbsp;</p>
<p>InsightBaseAI is able to understand and analyze your data even if it's complex and unstructured. Feel free to create an account, and connect your database to see it in action.</p>

How to architect your data to play well with AI systems

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Maximizing Your Application's Potential with AI-Optimized Data Architecture

<p>In today's rapidly evolving digital landscape, businesses are striving to become more data-driven to stay ahead of the competition. Traditional business intelligence tools have played a pivotal role in helping organizations make sense of their data, but there is a new player on the scene: artificial intelligence. As AI continues to make strides in various industries, it is set to revolutionize data analytics and unleash the true potential of business intelligence. In this blog post, we will delve into the future of BI and explore the various ways AI is transforming the data analytics landscape.</p>
<h3>&nbsp;</h3>
<h3>Enhanced Data Processing and Analysis:</h3>
<p>One of the primary ways AI is impacting data analytics is by enabling faster and more efficient processing of vast amounts of data. Through the use of machine learning algorithms and advanced analytics techniques, AI-powered BI tools can quickly sift through large datasets, identify patterns, and extract valuable insights. This not only saves time and resources but also allows organizations to make data-driven decisions at a much faster pace than before.</p>
<p>&nbsp;</p>
<h3>Improved Accuracy and Predictive Capabilities:</h3>
<p>Traditional BI tools often struggle with providing accurate predictions and forecasts due to the complexity of the data and the limitations of manual analysis. AI-powered BI tools, on the other hand, can leverage machine learning to identify trends and patterns, leading to more accurate and reliable forecasts. As a result, businesses can make better-informed decisions and allocate resources more effectively, ultimately enhancing their overall performance.</p>
<p>&nbsp;</p>
<h3>Natural Language Processing and Conversational Analytics:</h3>
<p>One of the most exciting developments in AI-powered BI is the integration of natural language processing (NLP). NLP allows users to interact with their BI tools using natural language, making it easier for non-technical users to access and understand complex data. Conversational analytics further expands on this concept by enabling users to ask questions and receive data-driven responses in real time. This democratizes access to data insights and empowers everyone within an organization to make data-driven decisions.</p>
<p>&nbsp;</p>
<h3>Advanced Data Visualization:</h3>
<p>AI is also revolutionizing the way businesses visualize and present their data. By leveraging AI algorithms, BI tools can automatically generate advanced visualizations that help users better understand the insights hidden within their data. Moreover, these visualizations can be interactive, allowing users to explore the data further and gain deeper insights into the trends and patterns that may impact their decision-making.</p>
<p>&nbsp;</p>
<h3>AI-Driven Automation:</h3>
<p>As AI continues to advance, it is likely that we will see more automation in the field of data analytics. This may involve the automated generation of reports, real-time alerts based on predefined thresholds, and even automated decision-making in specific business scenarios. By automating these processes, organizations can save time and resources, allowing them to focus on more strategic initiatives.</p>
<p>&nbsp;</p>
<p>The integration of AI into business intelligence is undoubtedly shaping the future of data analytics. With the potential to enhance data processing, improve accuracy, enable natural language interaction, and automate various aspects of the analytics process, AI-powered BI tools are set to become indispensable for organizations looking to stay competitive in the digital age. By embracing this new wave of AI-driven analytics, businesses can unlock the full potential of their data and make smarter decisions that drive growth and innovation.</p>

How AI Will Revolutionize Data Analytics by Providing Better and Deeper Data Insights

Introducing DBAQL

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What is Business Intelligence?