<div>
<p>Windows Server 2008 Tableau Desktop 7.0 Local MySQL database using Xampp</p>
<p>When attempting to connect to a localhost MySQL database server using the native MySQL data connection in Tableau Desktop, I'm getting the following error:</p>
<p>"The connection to the data source might have been lost. Communication with the Tableau Protocol Server process was lost.</p>
<p>Unable to connect to the server "localhost". Check that the server is running and that you have access privileges to the requested database. Unable to connect to the server. Check that the server is running and that you have access privileges to the requested database."</p>
<p>When using "Other Databases (ODBC)" in Tableau, I am able to connect and return data. However, I would prefer to use the MySQL connection to avoid the limitations of the Other Databases connection.</p>
<p>I created a specific username in phpmyadmin as well as tried using the root username and password and the same error was returned. I created a user DSN in odbcad32.exe and attempted using multiple versions of the MySQL ODBC driver (3.5, 5.2.7, 5.3.4).</p>
<p>Does anyone have any ideas of what might be causing the error? Really appreciate any help.</p>
</div>
<div>
<div>
<div>
<div>In Addition, I learn from <a href="https://www.igmguru.com/data-science-bi/tableau-training/">T</a><span><a href="https://www.igmguru.com/data-science-bi/tableau-training/">ableau certification course</a>.</span></div>
<div> </div>
<div>Thank you in advance.</div>
</div>
</div>
</div>

Tableau error connecting to local MySQL db


<p>I have a Keras ML model .h5 file that I would like to publish as a web service. This model was created in Databricks. I want to use Azure ML for this purpose. I am following the steps given in this Azure documentation.</p>
<p>One of the prerequisites is to have "Azure Machine Learning SDK". All these topics are discussed in the Ai ml Certification.</p>
<p>My question is how to install "Azure Machine Learning SDK" in my Azure ml workspace. Do I need to type the commands in the Cloud Shell?</p>
<p>Any pointers would be helpful. Thanks.</p>

How to use an existing machine learning model with Azure Machine Learning?

<p>Open your SQL query and navigate to line 62. Look for any references to Field1 at or near the 33rd character of that line. You should check if Field1 is referenced without specifying which table it belongs to. Ensure that all your field names are fully qualified with their respective table aliases.</p>

<p>In Tableau, the notation "[62:33]" in the error message is used to indicate the specific location within your Custom SQL Query where the error occurred. It provides a way to pinpoint the line and character position in your query where Tableau encountered a problem. Here's how to interpret it:</p>
<ul>
<li>
<p><strong>62</strong>: This number represents the line number in your Custom SQL Query where the error occurred. In this case, the error is on line 62 of your query.</p>
</li>
<li>
<p><strong>33</strong>: This number represents the character position within line 62 where the error was encountered. It indicates that the issue occurred 33 characters into line 62.</p>
</li>
</ul>
<p>So, in your specific error message, Tableau is telling you that there's an issue related to the "Field1" name being ambiguous, and it's located at line 62, character position 33 in your Custom SQL Query.</p>
<p>To track down the error and resolve it, you'll want to go to line 62 in your SQL query and review the code around character position 33. The ambiguity in the "Field1" name likely means that Tableau is having trouble determining which table or data source "Field1" is referring to within your query. You might need to provide more specific table aliases or adjust your query to make it unambiguous.</p>

<div>
<p>In Tableau I received the following error message:</p>
<p>The Google BigQuery service was unable to compile the query. Name Field1 is ambiguous inside Custom SQL Query at [62:33]</p>
<p>My BQ Query seems to work fine in BQ, but when copy paste in Tableau the above error shows. In order for me to track the error, I want to understand the error message.</p>
<p>What does <strong>[62:33]</strong> refer to? My query is only 47 lines of code, so I can't really seem to grasp the meaning of this notation...</p>
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<div>
<div> </div>
<div>Thank you in advance.</div>
</div>

Tableau error notation in brackets meaning

<p>Hy Guys,</p>
<p><strong>CCSP Course</strong></p>
<p>With the help of this<a href="https://www.igmguru.com/cyber-security/ccsp-isc2-certification-training/"> CCSP online training certification course</a>, develop your knowledge of cloud security architecture, design, applications, and operations. You will get step-by-step instructions and a comprehensive lesson plan that is simple to follow covering every aspect of the CCSP, which will help you further your career in the expanding sector of cloud security.</p>

Digital Trainer

<p>Hi</p>
<p>I am using built in functions and libraries for this <a href="https://www.igmguru.com/data-science-bi/python-training/">python </a>code and I am trying to execute this code, but it is showing <strong>NameError.</strong></p>
<p> </p>
<div><code>import</code> <code>time</code></div>
<div><code>  </code> </div>
<div><code># slower (Without map())</code></div>
<div><code>start </code><code>=</code> <code>time.clock() </code></div>
<div><code>s </code><code>=</code> <code>'geeks'</code></div>
<div><code>U </code><code>=</code> <code>[]</code></div>
<div><code>for</code> <code>c </code><code>in</code> <code>s:</code></div>
<div><code>    </code><code>U.append(c.upper())</code></div>
<div><code>print</code> <code>(U)</code></div>
<div><code>elapsed </code><code>=</code> <code>time.clock()</code></div>
<div><code>e1 </code><code>=</code> <code>elapsed </code><code>-</code> <code>start</code></div>
<div><code>print</code> <code>(</code><code>"Time spent in function is: "</code><code>, e1)</code></div>
<div><code>  </code> </div>
<div><code># Faster (Uses builtin function map())</code></div>
<div><code>s </code><code>=</code> <code>'geeks'</code></div>
<div><code>start </code><code>=</code> <code>time.clock() </code></div>
<div><code>U </code><code>=</code> <code>map</code><code>(</code><code>str</code><code>.upper, s) </code></div>
<div><code>print</code> <code>(U)</code></div>
<div><code>elapsed </code><code>=</code> <code>time.clock()</code></div>
<div><code>e2 </code><code>=</code> <code>elapsed </code><code>-</code> <code>start</code></div>
<div><code>print</code> <code>(</code><code>"Time spent in builtin function is: "</code><code>, e2)</code></div>
<p> </p>
<p>Thanks.</p>

Python Code Error

<p>The cost of Robotic Process Automation (RPA) certification can vary widely depending on several factors, including the certification provider, the level of certification, and your location. Here are some general guidelines:</p>
<ul>
<li>Certification Provider: Different organizations and vendors offer RPA certifications. Some of the popular ones include UiPath, Blue Prism, Automation Anywhere, and Microsoft. Each of these providers may have their own pricing structure for certification exams and training materials.</li>
<li>Certification Level: RPA certifications often come in different levels, such as beginner, intermediate, and advanced. The cost of certification may increase with the level of expertise being tested. For example, an entry-level certification might be less expensive than an advanced certification.</li>
<li>Training Materials: In addition to the exam fee, you may need to invest in training materials, courses, and study resources to prepare for the certification. These additional costs can vary depending on the provider and your chosen method of study.</li>
<li>Location: The cost of certification exams can also vary by region. Some regions may have lower or higher exam fees based on local market conditions.</li>
<li>Promotions and Discounts: Some certification providers offer promotions, discounts, or bundle deals that can reduce the overall cost of certification.</li>
</ul>
<p>To get the most accurate and up-to-date information on the cost of RPA certification, it's recommended to visit the official website of the certification provider you're interested in or contact their customer support. They will provide you with specific pricing details for the certification program you wish to pursue. Additionally, you can check if there are any community colleges, universities, or online platforms that offer RPA courses and certification at a lower cost compared to vendor-specific certifications.</p>
<p> </p>
<p> </p>

What is the cost of RPA certification?

<p>The amount of training data required for machine learning can vary depending on several factors, including the complexity of the task, the complexity of the model, and the quality of the data. In general, having more diverse and representative training data tends to improve the performance of machine learning models<a href="https://fnafpro.io">.</a></p>
<p>However, there is no fixed rule for the exact amount of training data needed. Some machine learning algorithms can achieve reasonable performance with a few hundred or thousand labeled examples, while others may require millions of examples. It also depends on the dimensionality of the data and the complexity of the patterns to be learned.</p>

How much training data is required for machine learning?

<p>Yes, it’s definitely possible—especially if you're using labeled data to validate or evaluate unsupervised models. Techniques like clustering can help identify hidden structures even when labels are present, and later you can compare results against known outcomes. It’s not traditional, but it can surface patterns and anomalies you might otherwise overlook in a purely supervised setup.</p>
<p> </p>
<p> </p>
<p> </p>
<p> </p>

Is it possible to use unsupervised learning for labeled data?

<p><strong>Data Profiling in ETL</strong></p>
<p>The ETL data source is a collection of detailed data. It seeks to understand the structure, value, and significance of information and its relation to other information. This is done through Extraction, Conversion, and Upload (ETL) and helps companies find the information they need for their purposes.</p>

<p>Data profiling in the context of ETL (Extract, Transform, Load) refers to the process of analyzing and understanding the structure, quality, and content of the source data before it is transformed and loaded into a target system. Data profiling helps to uncover inconsistencies, anomalies, and patterns within the data, and it provides insights that are crucial for designing effective ETL processes<a href="https://hello-neighbor.online">.</a></p>

<p>Hello</p>
<p>Thanks Zaid md,</p>
<p>Data profiling in ETL is the process of analyzing and assessing the quality and structure of source data before it is loaded into a data warehouse or repository. The purpose is to identify potential data quality issues, define rules and transformations, and ensure the accuracy, completeness, and consistency of the data. By performing data profiling, organizations can make informed business decisions and improve the overall quality of their data.</p>

Software Developer

What is data profiling in ETL?

<p>Yes, there are several free and open source image recognition APIs available:</p>
<p>Clarifai - An open source image and video recognition API. It has a generous free tier.</p>
<p>Amazon Rekognition - Amazon's image and video analysis service. Has a free tier that offers 5,000 transactions per month.</p>
<p>Microsoft Computer Vision - Provides image analysis and description. The free tier offers 5,000 transactions per month.</p>
<p>Google Cloud Vision API - Google's image recognition service. The free tier offers 1,000 requests per month.</p>
<p>OpenCV - A popular computer vision and machine learning software library. Can be used to build custom image recognition models and applications.</p>
<p>Tensorflow/Keras - Deep learning frameworks that can be used with transfer learning to build image classifiers. Free to use and open source.</p>
<p>IBM Watson Visual Recognition - IBM's visual recognition service. The free tier offers 50 API calls per month.</p>
<p>Alteryx Computer Vision - A library of computer vision tools for tasks like object detection, image classification etc. Open source.</p>
<p>DeepDetect - A framework for deep learning microservices including image recognition. Free for non-commercial use.</p>
<p>Cloudsight - Provides image recognition via a REST API. The free tier allows 1,000 API calls per month. </p>
<p>So in summary, Clarifai, Amazon Rekognition, OpenCV and libraries like Tensorflow offer the most full-featured free open source options.</p>

Is there any free open source image recognition API?

<p>OLAP (Online Analytical Processing) databases and relational databases are both types of database systems, but they serve different purposes and have distinct characteristics.</p>
<ol>
<li>
<p><strong>Data Model:</strong></p>
<ul>
<li>
<p><strong>Relational Database:</strong> Relational databases are based on the relational model, which organizes data into tables with rows and columns. Each table has a unique key, and relationships between tables are established using foreign keys.</p>
</li>
<li>
<p><strong>OLAP Database:</strong> OLAP databases use a multidimensional data model. Instead of tables, they organize data into dimensions and measures. Dimensions represent the characteristics or categories of data, and measures represent the data values.</p>
</li>
</ul>
</li>
<li>
<p><strong>Purpose:</strong></p>
<ul>
<li>
<p><strong>Relational Database:</strong> Relational databases are designed for transactional processing (OLTP - Online Transaction Processing). They are optimized for efficient insertion, updating, and retrieval of individual records.</p>
</li>
<li>
<p><strong>OLAP Database:</strong> OLAP databases are designed for analytical processing (OLAP - Online Analytical Processing). They are optimized for complex queries and aggregations on large datasets to <strong>support business intelligence</strong> and decision-making.</p>
</li>
</ul>
</li>
<li>
<p><strong>Query Performance:</strong></p>
<ul>
<li>
<p><strong>Relational Database:</strong> Relational databases excel in handling simple queries involving individual records or small sets of records. They may struggle with complex analytical queries or aggregations on large datasets.</p>
</li>
<li>
<p><strong>OLAP Database:</strong> OLAP databases are specifically designed for complex queries and aggregations. They can efficiently handle multidimensional queries, making them suitable for analytical tasks.</p>
</li>
</ul>
</li>
<li>
<p><strong>Data Aggregation:</strong></p>
<ul>
<li>
<p><strong>Relational Database:</strong> Aggregations in relational databases can be computationally expensive, especially when dealing with large datasets, as they involve scanning and summarizing numerous records.</p>
</li>
<li>
<p><strong>OLAP Database:</strong> OLAP databases are optimized for data aggregation. They store pre-aggregated data at different levels of granularity, allowing for faster retrieval of summarized information.</p>
</li>
</ul>
</li>
<li>
<p><strong>Schema:</strong></p>
<ul>
<li>
<p><strong>Relational Database:</strong> Relational databases use a schema with predefined tables and relationships. The schema is typically normalized to eliminate redundancy.</p>
</li>
<li>
<p><strong>OLAP Database:</strong> OLAP databases often use a star or snowflake schema. Data is organized into a central fact table (containing measures) surrounded by dimension tables (containing attributes). This allows for efficient querying and aggregation along dimensions.</p>
</li>
</ul>
</li>
</ol>
<p>In summary, while both OLAP and relational databases store and manage data, their design and optimization are geared toward different types of applications. Relational databases are well-suited for transactional processing, while OLAP databases are designed to efficiently handle complex analytical queries and aggregations for business intelligence purposes</p>

<p><strong>Relational Database (RDBMS)</strong></p>
<ul>
<li>RDBMS is a DBMS that enables the organization of aggregated data.</li>
<li>Relational DBMS is the most widely used database like Oracle, SQL Server. It is characterized by handling data in tables with basic keys that make it possible to identify the rows in each table separately. And an external key that allows you to associate the table with other tables.</li>
</ul>
<p><strong>OLAP (Online Analytical Processing)</strong></p>
<ul>
<li>OLAP is a collection of software tools that provide information to business decision-makers.</li>
<li>OLAP usually works on a standardized database to facilitate OLAP, not OLTP. These databases are often referred to as data warehouses.</li>
<li>You can check the comparison and key differences between <a href="https://mindmajix.com/oltp-vs-olap">OLAP vs OLTP</a> here</li>
</ul>

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