Implementing Data Engineering Solutions Using Microsoft Fabric (Cert Exam DP-700)

Colleagues, the “DP-700 Certification” program validates your ability to design, build, secure, and optimize end to end data engineering solutions using Microsoft Fabric, covering key workloads such as data ingestion, transformation, orchestration, Lakehouse and Warehouse implementation, realtime intelligence, and performance optimization. It focuses on practical, enterprise-grade data engineering skills using technologies like SQL, PySpark, Kusto Query Language (KQL), Fabric notebooks, pipelines, Lakehouses, Warehouses, and OneLake, assessing your capability to support analytics, BI, and AI workloads across an organization. You will learn to: Configure workspace settings in Microsoft Fabric, including Spark, domain, OneLake, and data workflow settings to ensure optimal performance and organization. Master data ingestion and transformation processes using SQL, PySpark, and Kusto Query Language (KQL) to prepare data for analysis. Develop skills to monitor and optimize data solutions, ensuring efficient and reliable data operations. Learn to design and implement data storage solutions that support scalable and secure data management. Understand and apply data security measures to protect sensitive information and ensure compliance with industry standards. And gain the ability to troubleshoot and resolve data-related issues, ensuring the integrity and availability of data for business intelligence. Skill-based lessons address: 1) Introduction to Microsoft Fabric Data Engineering, 2) Configure Fabric Workspaces, 3) Implement Lifecycle Management, 4) Configure Security and Governance, 5) How to Orchestrate Fabric Items, 6) Design and Implement Loading Patterns, 7) Ingest and Transform Batch Data, 8) Ingest and Transform Streaming Data, 9) Monitor Fabric Items, 10) Identify and Resolve Errors, 11) Optimize Performance, and 12) Practical Applications and Case Studies.

Enroll today!: Teams and executives are welcome: https://tinyurl.com/3spyakbt

Recommended Reading: “Data-Driven Organizations” series.

1 - The Promise of Data-Driven Decision-Making  (Audible) (Kindle)

2 - Implementing Data Science Methodology: From Data Wrangling to Data Viz (Audible) (Kindle)

3 - “The Upskill Gambit - Discover the 5 Keys to Your Career and Income Security in the Digital Age” (Audible) (Kindle)

Much career success from the Data Science Academy (please subscribe and share with your colleagues)

Python for Data Science, AI & Development (IBM)

Colleagues, the “Python for Data Science, AI & Development - IBM” program will take you from zero to programming in Python in a matter of hours—no prior programming experience is necessary! You’ll begin with Python basics, including data types, expressions, variables, and string operations. You will explore essential data structures such as lists, tuples, dictionaries, and sets, learning how to create, access, and manipulate them. Next, you will delve into logic concepts like conditions and branching, learning how to use loops and functions, along with important programming principles like exception handling and object-oriented programming. Training lessons include: 1) Python Basics, 2) Python Data Structures, 3) Python Programming Fundamentals, 4) Working with Data in Python, and 5) APIs and Data Collection. You will learn to: Develop a foundational understanding of Python programming by learning basic syntax, data types, expressions, variables, and string operations. Apply Python programming logic using data structures, conditions and branching, loops, functions, exception handling, objects, and classes. Demonstrate proficiency in using Python libraries such as Pandas and Numpy and developing code using Jupyter Notebooks. Access and extract web-based data by working with REST APIs using requests and performing web scraping with BeautifulSoup. And gain highly marketable skills with Data Import/Export, Data Analysis, Scripting, and Data Collection.

Enroll today!: Teams and executives are welcome: https://edx.sjv.io/gReEY5

Listen today via Amazon Audible (https://tinyurl.com/ydbyh2t9) 

Or read now on Kindle (https://tinyurl.com/hptundzs) 

These books are part of the “Data-Driven Organizations” series.

1 - The Promise of Data-Driven Decision-Making  (Audible) (Kindle)

2 - Implementing Data Science Methodology: From Data Wrangling to Data Viz (Audible) (Kindle)

3 - “The Upskill Gambit - Discover the 5 Keys to Your Career and Income Security in the Digital Age” (Audible) (Kindle)

Much career success from the Data Science Academy (please subscribe and share with your colleagues)

Data Science (HarvardX)

Colleagues, the “Data Science” program from  HarvardX prepares you with the necessary knowledge base and useful skills to tackle real-world data analysis challenges. The program covers concepts such as probability, inference, regression, and machine learning and helps you develop an essential skill set that includes R programming, data wrangling with dplyr, data visualization with ggplot2, file organization with Unix/Linux, version control with git and GitHub, and reproducible document preparation with RStudio. In each course, we use motivating case studies, ask specific questions, and learn by answering these through data analysis. Case studies include: Trends in World Health and Economics, US Crime Rates, The Financial Crisis of 2007-2008, Election Forecasting, Building a Baseball Team (inspired by Moneyball), and Movie Recommendation Systems. You will learn Fundamental R programming skills, Statistical concepts such as probability, inference, and modeling and how to apply them in practice, Gain experience with the tidyverse, including data visualization with ggplot2 and data wrangling with dplyr, Become familiar with essential tools for practicing data scientists such as Unix/Linux, git and GitHub, and RStudio, Implement machine learning algorithms, and In-depth knowledge of fundamental data science concepts through motivating real-world case studies. The 9 courses that comprise this program include: 1) R Basics, 2) Visualization, 3) Probability, 4) Inference and Modeling, 5) Productivity Tools, 6) Wrangling, 7) Linear Regression, 8) Building Machine Learning Models, and 9) Capstone Project.

Enroll today!: Teams and executives are welcome: https://edx.sjv.io/9LVMxy

Recommended Reading: “Data-Driven Organizations” series.

1 - The Promise of Data-Driven Decision-Making  (Audible) (Kindle)

2 - Implementing Data Science Methodology: From Data Wrangling to Data Viz (Audible) (Kindle)

3 - “The Upskill Gambit - Discover the 5 Keys to Your Career and Income Security in the Digital Age” (Audible) (Kindle)

Much career success from the Data Science Academy (please subscribe and share with your colleagues)

ChatGPT + Excel: AI-Enhanced Data Analysis & Insight Specialization

Colleagues, in the “ChatGPT + Excel: AI-Enhanced Data Analysis & Insight Specialization” program you will learn to: 1) Turn Text into Data: Extract structured datasets from unformatted text or images with ChatGPT.Example: Convert a messy list of LinkedIn posts into a clean table with post titles, dates, and engagement stats, 2) Create Formulas: Generate complex formulas tailored to solve specific challenges, even if you don’t know how to write them from scratch, 3) Design Stunning Visualizations: Build engaging charts and graphs directly from your prompts or replicate a chart from a photo. Example: Transform a hand-drawn sales graph into a professional Excel chart in seconds, 4) Merge and Unify Datasets: Seamlessly combine data from multiple Excel sheets or CSV files into one cohesive table. Example: Integrate customer data with sales records to track performance by demographic or region, 5) Automate with VBA Scripts: Create powerful macros with ChatGPT to eliminate repetitive tasks and enhance productivity, 6) Turn Images Into Excel Solutions: Use ChatGPT to turn a photo of a whiteboard into an Excel-based project plan or inventory tracker. Example: Snap a photo of a brainstorming session and convert it into a structured Excel sheet, and 7) Craft Data-Driven Stories: Build narratives that make your data compelling and actionable for presentations. Skill-based training modules include: ChatGPT + Excel: Master Data, Make Decisions, Tell Stories, ChatGPT + Excel: Master AI-driven Formulas & Visualizations, and Prompt Engineering for ChatGPT. You will also gain highly marketable skills with: Plot (Graphics), Data Visualization, Prompt Patterns, Spreadsheet Software, Data Presentation, LLM Application, Data Analysis, AI Literacy, Excel Formulas, Consolidation, Data Storytelling, Excel Macros, Data Synthesis, Storytelling, AI powered creativity, and AI Enablement. And you will use tools: Prompt Engineering, Microsoft Excel, Generative AI, and ChatGPT. 

Enroll today!: Teams and executives are welcome: https://imp.i384100.net/VOK7aJ 

Listen today via Amazon Audible (https://tinyurl.com/ydbyh2t9) 

Or read now on Kindle (https://tinyurl.com/hptundzs) 

This book is part of the “Data-Driven Organizations” series.

1 - The Promise of Data-Driven Decision-Making  (Audible) (Kindle)

2 - Implementing Data Science Methodology: From Data Wrangling to Data Viz (Audible) (Kindle)

3 - “The Upskill Gambit - Discover the 5 Keys to Your Career and Income Security in the Digital Age” (Audible) (Kindle)

Much career success from the Data Science Academy (please subscribe and share with your colleagues)

The Power of Statistics (Google)

Colleagues, in the “The Power of Statistics” from Google you will discover how data professionals use statistics to analyze data and gain important insights. You'll explore key concepts such as descriptive and inferential statistics, probability, sampling, confidence intervals, and hypothesis testing. You'll also learn how to use Python for statistical analysis and practice communicating your findings like a data professional. By the end of this course, you will: Describe the use of statistics in data science. Use descriptive statistics to summarize and explore data. Calculate probability using basic rules. Model data with probability distributions. Describe the applications of different sampling methods. Calculate sampling distributions. Construct and interpret confidence intervals. Conduct hypothesis tests. You will also gain hands-on skills with Probability Distribution, Statistics, Probability and Statistics, Sampling (Statistics), Descriptive Statistics, Probability, Statistical Methods, Statistical Hypothesis Testing, Analytics, Advanced Analytics, Statistical Programming, Statistical Inference, Statistical Analysis, A/B Testing, Data Analysis, and Data Science. And use skills in Python Programming, Introduction to Statistics with Python, Probability, Sampling, Confidence Intervals, Introduction to Hypothesis Testing, and Capstone Project.

Enroll today!: Teams and executives are welcome: https://imp.i384100.net/9VjY14

Recommended Readings: The “Data-Driven Organizations” series.

1 - The Promise of Data-Driven Decision-Making  (Audible) (Kindle)

2 - Implementing Data Science Methodology: From Data Wrangling to Data Viz (Audible) (Kindle)

3 - “The Upskill Gambit - Discover the 5 Keys to Your Career and Income Security in the Digital Age” (Audible) (Kindle)

Much career success from the Data Science Academy (please subscribe and share with your colleagues)

Data Analysis: Basic Probability and Statistics (HarvardX)

Colleagues, the “Data Analysis: Basic Probability and Statistics” training from HarvardX will increase your quantitative reasoning skills through a deeper understanding of probability and statistics, with the engaging "Fat Chance" approach that's made this course a favorite among learners worldwide.You will learn to: Solve combinatorial counting problems, Solve problems using basic and advanced probability, The normal distribution and its many statistical applications, and Recognize common fallacies in probability, as well as some of the ways in which statistics are abused or simply misunderstood. Skill-based lessons include: 1) Basic Counting - Counting Numbers, Large Numbers, The Multiplication Principle, More on the Multiplication Principle and Factorials, The Subtraction Principle, Advanced Counting; 2) Counting Collections - Binomial Coefficients, Applications of Collections, Multinomials, Collections with Repetition; 3) Basic Probability - Flipping Coins, Rolling Dice, Playing Poker, Distributions of Bridge Hands,; 4) Expected Value - Chuck-A-Luck, Slot Machines, Strategizing; 5) Conditional Probability - The Monty Hall Problem, Set-Up and Examples, Elections; 6) Bernoulli Trials, The Gambler's Ruin; 7) The Normal Distribution - Games, Games: Examples and Variance, Iterating Games, The Normal Distribution - Part 1 and 2.

Enroll today!: Teams and executives are welcome: https://edx.sjv.io/gReEY5

Listen today via Amazon Audible (https://tinyurl.com/ydbyh2t9) 

Or read now on Kindle (https://tinyurl.com/hptundzs) 

These books are part of the “Data-Driven Organizations” series.

1 - The Promise of Data-Driven Decision-Making  (Audible) (Kindle)

2 - Implementing Data Science Methodology: From Data Wrangling to Data Viz (Audible) (Kindle)

3 - “The Upskill Gambit - Discover the 5 Keys to Your Career and Income Security in the Digital Age” (Audible) (Kindle)

Order today and much career success from the Data Science Academy (please subscribe and share with your colleagues)

Implementing Data Engineering Solutions Using Azure Databricks (Certification Exam DP-750)

Colleagues, the DP-750 exam validates the modern Azure Databricks toolkit: Lakeflow Spark Declarative Pipelines for low-code pipeline authoring, Lakeflow Connect for managed ingestion, Lakeflow Jobs for orchestration, Unity Catalog for fine-grained access control and lineage, AI/BI Genie for natural-language data discovery, Databricks Asset Bundles for CI/CD, and Photon for query acceleration. Newer features the exam emphasizes--liquid clustering, attribute-based access control, deletion vectors, and structured streaming with Auto Loader--reflect where production data engineering is heading. This certification matters because organizations are consolidating fragmented data stacks onto governed lakehouses, and Microsoft is signaling that Azure Databricks fluency is now a distinct, certifiable specialty alongside Fabric and Synapse skills. Learn How To: Provision and configure an Azure Databricks workspace, choose appropriate compute for the task at hand, and work fluently in notebooks across SQL and Python. Design and build the Unity Catalog object model--catalogs, schemas, volumes, tables, views, materialized views, foreign catalogs--with naming and isolation patterns that survive contact with production. Secure and govern data using the full Unity Catalog toolkit: privilege grants, row filters, column masks, attribute-based access control, service principals, managed identities, Key Vault-backed secrets, lineage tracking, audit logs, retention policies, and Delta Sharing. Reason about lakehouse data design--Delta Lake fundamentals, file formats, partitioning, liquid clustering, slowly changing dimensions, temporal tables, and the medallion architecture--as the conceptual backbone of every pipeline. Ingest data through every supported path: Lakeflow Connect, notebook-based ingestion, SQL methods, change data capture, Spark Structured Streaming, Azure Event Hubs, and Auto Loader. Cleanse, profile, and transform data using the full transformation toolkit, then enforce quality with validation checks, schema management, and pipeline expectations. Build and ship production pipelines using Lakeflow Spark Declarative Pipelines and Lakeflow Jobs, with proper Git workflow, a complete testing strategy, and Asset Bundles for deployment via CLI or REST API. Monitor, troubleshoot, and optimize workloads using the Spark UI, DAG analysis, OPTIMIZE/VACUUM, and Azure Monitor with Log Analytics. Approach the DP-750 exam with the conceptual reasoning skills its scenario-based question format demands. Lessons address: 1) Foundations: Workspaces, Compute, and Notebooks, 2) Unity Catalog: Structure, Security, and Governance, 3) Designing Data for the Lakehouse, 4) Ingesting and Transforming Data, and 5) Production Pipelines and Operations.

Enroll today!: Teams and executives are welcome: https://tinyurl.com/yyyrbzp3

Listen today via Amazon Audible (https://tinyurl.com/ydbyh2t9) 

Or read now on Kindle (https://tinyurl.com/hptundzs) 

This book is part of the “Data-Driven Organizations” series.

1 - The Promise of Data-Driven Decision-Making  (Audible) (Kindle)

2 - Implementing Data Science Methodology: From Data Wrangling to Data Viz (Audible) (Kindle)

3 - “The Upskill Gambit - Discover the 5 Keys to Your Career and Income Security in the Digital Age” (Audible) (Kindle)

Much career success from the Data Science Academy (please subscribe and share with your colleagues)