BigQuery Metastore, AI-Driven Data Dashboard Prototype, Native Execution in Microsoft FabricStart PII Leak Detection and Data Flow Mapping Where It Matters Most: In the Code92% of breaches in 2023 involved PII. HoundDog bridges AppSec and Data Security with an ultra-fast, lightweight static code scanner that detects PII leaks early, preventing costly fixes later.It automates compliance for frameworks like HIPAA, PCI, GDPR, and FedRAMP, ensuring PII safety from development to deployment. Trusted by Fortune 500s, HoundDog enables shift-left PII prevention with IDE plug-ins and CI/CD integration. Book a demo now to see how HoundDog can streamline your security and compliance efforts!Book a Live DemoSponsored📬 Welcome to BIPro #88– Your Weekly Business Intelligence Boost! 🚀We’re back from the holiday break! We hope you've missed our updates as much as we've missed sharing them with you 😊. We’ve also been working on something exciting to make your learning journey effortless, and we’d love for you to help co-create it with us!Take a quick moment to fill out this survey, and as a thank-you, you'll get access to a free ebook on the AI Crash Course. Now, let’s jump right in! This week, we’re exploring cutting-edge trends and tools to supercharge your data strategy. From Riveron’s exciting new partnership with Alteryx to building apps with the Microsoft Fabric API, we’ve got insights that will elevate your BI game. Plus, we’ve got tips on improving data readiness, enhancing data visualization, and so much more! Let’s dive in 👇Top Insights:➽Survey Reveals Over 50% of AI Leaders Plan to Augment Hyperscaler AI Investments➽Riveron Announces Partnership with Alteryx➽How to Improve Data Readiness for Tableau Cloud➽Building Apps with Microsoft Fabric API for GraphQL➽Important Update coming to R and Python visuals in Power BI➽Boosting Data Accuracy: Resolving Common Data Quality Issues Using SQL➽Introducing BigQuery metastore fully managed metadata service➽Faster data processing with Native Execution Engines in Microsoft Fabric Runtime 1.3Dive in and let this week’s insights supercharge your BI journey! 🚀Design the Learning Journey You Want! 🌟 Help Us Make Your Learning Journey Even Better! 🌟As we mentioned earlier, we've got something exciting in the works to make your experience with Data Science, BI, and ML even easier, and we’d absolutely love for YOU to be a part of it!Your input will help us create the perfect learning experience for you! It’ll only take a few minutes, and as a thank-you, you’ll get full access to a free ebook on the AI Crash Course!👉 Take the Survey Now!Let's make learning even more amazing, together! 💡Take the Survey Now!Cheers,Merlyn ShelleyGrowth Lead, Packt📊 Data Viz Trends Shaping the Future of Insights⫸Riveron Announces Partnership with Alteryx: Riveron, a business advisory firm specializing in CFO and private equity services, partnered with Alteryx to enhance financial transformations using reporting and analytics tools. This collaboration aims to streamline processes, support data-driven decisions, and enable faster AI-powered business insights.⫸Metabase alternatives: peeking at other Business Intelligence tools: This article compares popular Business Intelligence tools like Metabase, Tableau, Power BI, Looker, Mode, Superset, Domo, and Quicksight. It outlines each tool's strengths, ideal users, and key features, with insights from community feedback, focusing on ease of use, cost, and deployment options.⫸How to Improve Data Readiness for Tableau Cloud: This blog outlines a four-step framework to improve data readiness for AI and self-service in Tableau: 1) Monitor data sources to assess their quality. 2) Identify meaningful objectives aligned with organizational goals. 3) Create and promote certified data assets. 4) Enable users by providing guidance and tools.⫸Building Apps with Microsoft Fabric API for GraphQL: This article highlights how Microsoft Fabric's GraphQL API enables the creation of data applications. It offers efficient data retrieval, flexibility, and single-endpoint access. The architecture leverages a medallion structure with data from the gold layer for analytics. Security is ensured via service principal authentication, and CI/CD pipelines automate app deployment.⫸Amazon QuickSight: 2024 year in review: Amazon QuickSight's 2024 innovations focused on AI, scalability, and user experience. Key features included Amazon Q for natural language data queries, scenario analysis, and unstructured insights. Enhanced visualizations, multi-source integration, and governance improvements were added. QuickSight's capabilities, including expanded regional support and deeper AI integration, empower businesses to analyze data faster and more efficiently.⫸Power BI January 2025 Feature Summary: Power BI's latest update introduces features like "Explore this data" for easier visualization exploration, enhanced Treemap visuals with new tiling methods, and semantic model version history for better management. Additionally, TMDL scripting (preview) allows users to script and modify models efficiently, along with other improvements to reporting and data connectivity.📈 Dive into Databases: SQL Essentials⫸Database Version Control with Git in Azure DevOps: This solution outlines how to use Azure DevOps and Git for version controlling SQL Server database scripts. By storing and backing up database code in Git, users can easily track changes and recover from data loss. The process involves creating a Git repository, writing a PowerShell script to generate and push SQL scripts, and using Azure DevOps for centralized storage and versioning. The solution improves database management and ensures secure, efficient tracking of SQL code changes over time.⫸Things I Wish I Knew as a DBA: This recorded webinar offers valuable insights from a seasoned DBA with over 20 years of experience, focusing on lessons learned from mistakes in areas such as corruption, backup and restore, managing expectations, performance, and security. Attendees will gain practical knowledge through demos and scripts, plus learn about dbWatch, a solution to automate key database management tasks.⫸JSON Data Type in Azure SQL Database: The article discusses the new native JSON data type in Azure SQL Database, offering improved storage efficiency and faster query performance. It covers using JSON functions for manipulation and compares the performance between the JSON data type and NVARCHAR(MAX).⫸Vector DB implementation using FAISS: This article demonstrates implementing an efficient document search system using FAISS (Facebook AI Similarity Search)and sentence embeddings. By leveraging the sentence-transformers library for embedding text and FAISS for vector database management, users can quickly retrieve relevant documents based on queries. The solution is ideal for applications like chatbots, document retrieval, and natural language understanding, and includes practical examples of integrating these technologies for semantic search.⫸Get Started With Vector Search in Azure Cosmos DB: This guide explains how to set up and use the Vector Search feature in Azure Cosmos DB for NoSQL. It walks through configuring a vector database, loading movie data with embeddings, and performing similarity searches in Python, TypeScript, Java, or .NET. The app uses the text-embedding-ada-002 model for vectorization.🔄 Real-World Transformation: How Gen BI Made Data Work⫸Behind the Scenes of a Successful Data Analytics Project: This article outlines a proven approach to tackling data projects. Key steps include defining the problem and objectives, setting expectations with stakeholders, preparing and cleaning data, performing exploratory analysis, building a data story, and ensuring actionable insights are shared and acted upon for meaningful business outcomes.⫸How Most Organizations Get Data & AI Strategy Wrongand How to Fix It? This article discusses the complexities of data strategy, addressing common misconceptions and offering a structured approach for organizations to leverage data effectively. It emphasizes that data strategy is not just about technical capabilities but needs to be integrated with business strategy, focusing on making strategic choices and fostering a data-driven culture.⫸Add Copilot Summaries to Power BI email subscriptions (Preview): The preview of Copilot summaries for Power BI report email subscriptions is now available for standard subscriptions on eligible capacities. This feature delivers insights on reports or specific pages via email. Users can opt-in, preview summaries, and test subscriptions, with some limitations on availability and report types.⫸Important Update coming to R and Python visuals in Power BI: Power BI service visuals will soon be upgraded with Python 3.11 and R 4.3.3, offering up to 2 vCores and updated libraries. Older Python (3.7.7) and R (3.4.4) versions will be retired. This update may affect existing visuals. Ensure compatibility by testing locally before rollout.⫸Charts, Dashboards, Maps, and More: Data Visualization in the Spotlight: This collection of articles covers various topics to elevate your data visualization and analysis skills. Highlights include tips on creating stunning charts, building effective dashboards, mastering geospatial data, and diving into advanced chart types like bump charts, plus AI insights and hands-on projects.⫸Sustainable Business Strategy with Data Analytics: This article explores how data analytics can help align diverse stakeholder interests in sustainability-driven supply chain decisions. It details how manufacturing plants can be strategically optimized for cost-efficiency and minimal environmental impact, using data models to balance production, logistics, and sustainability goals.⚡ Quick Wins: BI Hacks for Instant Impact⫸Enhance your Amazon Redshift business intelligence workloads with gen AI capabilities using Amazon Q in QuickSight: This article explains how Amazon QuickSight, paired with Amazon Redshift, empowers businesses to enhance their business intelligence workflows. It highlights Amazon Q, a feature that allows users to generate visualizations and insights through natural language queries, simplifying data access and decision-making.⫸JSON aggregates in Fabric Datawarehouse (Preview): This article introduces the preview of two powerful JSON aggregate functions in Fabric Data Warehouse: JSON_ARRAYAGG and JSON_OBJECTAGG. These functions simplify the creation of JSON arrays and objects from SQL data, improving query formatting and making it easier to represent complex data structures in JSON format.⫸Build SQL Server APIs Rapidly: In this webinar, DreamFactory CTO Jason Gilmore will showcase how to quickly generate secure, documented REST APIs for Microsoft SQL Server using DreamFactory’s platform. Topics include API generation, exposing stored procedures, data masking, and connecting SQL Server data to low-code dashboards and real-time reports. Attendees can try DreamFactory's SQL Server connector with a free 14-day trial.⫸Faster data processing with Native Execution Engines in Microsoft Fabric Runtime 1.3: This article introduces the Native Execution Engine for Fabric Spark, a new approach to memory management that improves data processing performance. By bypassing the JVM’s garbage collector, it reduces overhead and enhances memory allocation, offering faster data analytics with adaptive scaling and more stable performance without manual memory tuning.⫸Boosting Data Accuracy: Resolving Common Data Quality Issues Using SQL: This article explores how to handle common data quality issues in SQL, including NULL values, inconsistent data formats, invalid characters, duplicates, and non-ASCII characters. It offers practical SQL function examples to identify and resolve these problems, enhancing data integrity for better business insights and decision-making.⫸Introducing BigQuery metastore fully managed metadata service: This article introduces the BigQuery Metastore, a fully managed, scalable metadata service that supports interoperability across multiple data processing engines, including BigQuery, Apache Spark, Hive, and Flink. It helps unify data management and governance, enabling seamless access to data stored in various formats, such as Apache Iceberg, and simplifying metadata management in a lakehouse architecture. The service is serverless, requires no setup, and scales automatically, ensuring efficient data discovery, governance, and query processing at scale.🎤 Voices of BI: Lessons from Industry Experts⫸Survey Reveals Over 50% of AI Leaders Plan to Augment Hyperscaler AI Investments: A survey by DataRobot reveals that over 50% of AI leaders plan to increase investments in hyperscaler AI tools to address issues like interoperability, governance, scalability, security, and high costs. Despite investing heavily in hyperscaler AI, leaders face challenges scaling AI, validating security, and overcoming vendor lock-in. Many are seeking integrated AI solutions that reduce costs, ensure compliance, and accelerate AI initiatives. The DataRobot enterprise AI suite offers a customizable approach that accelerates AI use case delivery and reduces costs while improving security and compliance.⫸Tchibo brews up 10x faster customer insights with AlloyDB for PostgreSQL: Tchibo, a German coffee retailer, boosted customer feedback analysis by adopting AlloyDB for PostgreSQL. The solution improved query speeds from 10 seconds to one, enabling real-time insights. With AI-driven tools like "Customer Voice," Tchibo enhanced decision-making, reduced operational overhead, and positioned itself for scalable growth and innovation.⫸OpenAI Introduces Operator research preview: The newly released Operator is an AI agent that automates tasks on the web. Powered by the Computer-Using Agent (CUA), it interacts with graphical interfaces to perform actions like filling forms or ordering groceries. Initially available to Pro users in the U.S., it aims to expand based on feedback.⫸How to Build a Data Dashboard Prototype with Generative AI? This tutorial demonstrates how to create an interactive data dashboard using Goodreads reading data. It shows how to generate charts with Vizro-AI using natural language prompts and integrate them into a Jupyter Notebook. The resulting dashboard visualizes book reading timelines, reading velocity, and reviews comparison.⫸Optimising Budgets With Marketing Mix Models In Python: This article is the third part of a series on marketing mix modeling (MMM). It covers using MMM to optimize marketing budgets, explaining key concepts like response curves and linear programming. It also includes a hands-on Python tutorial for simulating data, training a model, validating it, and performing budget optimization.⫸The Basics you Must Master Before Diving into Marketing & Product Analytics: This article compares Product Analytics and Marketing Analytics, outlining their key differences in objectives, teams involved, tools used, and KPIs. It emphasizes how both disciplines play a critical role in driving growth, with Product Analytics focusing on user interactions and Marketing Analytics optimizing acquisition campaigns.We’ve got more great things coming your way, see you soon!*{box-sizing:border-box}body{margin:0;padding:0}a[x-apple-data-detectors]{color:inherit!important;text-decoration:inherit!important}#MessageViewBody a{color:inherit;text-decoration:none}p{line-height:inherit}.desktop_hide,.desktop_hide table{mso-hide:all;display:none;max-height:0;overflow:hidden}.image_block img+div{display:none}sub,sup{font-size:75%;line-height:0} @media (max-width: 100%;display:block}.mobile_hide{min-height:0;max-height:0;max-width: 100%;overflow:hidden;font-size:0}.desktop_hide,.desktop_hide table{display:table!important;max-height:none!important}}
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