My Skills

Data Analytics

Data Visualizations

  • Tableau Desktop [certificate]
    • I have expert-level skills in Tableau. I primarily use Tableau Desktop for creating dashboards and conducting in-depth analyses because of my extensive familiarity with the program and my strong preference for utilizing parameters, which greatly simplify workflows.

      My Tableau Expertise Includes:
      • Table Calculations: Skilled in creating and optimizing table calculations for advanced analytics.
      • Calculated Fields: Proficient in designing complex calculated fields to derive actionable insights.
      • Parameters: Expert in using parameters to add interactivity and flexibility to dashboards.
      • Level of Details (LOD) Calculations: Experienced in creating detailed and aggregated views for precise data analysis.
      • Filters:
        • Extract filters
        • Data source filters
        • Context filters
      • Advanced Dashboarding: Skilled in creating dynamic and interactive dashboards using containers for enhanced user experiences.
      • Web Integration: Experienced in embedding Tableau dashboards into web applications using Connected Apps and JWT.
      • Additional Capabilities:
        Familiar with a wide range of Tableau’s advanced features to meet diverse business needs.

        My mastery of Tableau allows me to efficiently transform complex datasets into visually compelling and actionable insights, empowering data-driven decision-making across organizations.
        You can find the dashboard I created here
  • Tableau Prep
    • I use Tableau Prep when the source data requires cleaning or transformation before being used in Tableau. I am proficient in leveraging scripts within Tableau Prep for advanced data preparation, enabling me to ensure that the data is optimized and ready for analysis and visualization. This capability helps streamline workflows and enhances the overall efficiency of my Tableau projects.
  • Microsoft PowerBI [certificate]
    • I have expert-level skills in Power BI. My expertise allows me to create dynamic, insightful, and interactive reports and dashboards that drive data-driven decision-making.

      My Power BI Expertise Includes:
      • Data Analysis Expressions (DAX): Proficient in crafting advanced DAX formulas to perform calculations and derive meaningful insights.
      • Power Query: Skilled in data transformation and preparation using Power Query to clean and shape data efficiently.
      • Context Filters Using DAX: Experienced in managing context filters to create precise and customized data views.
      • Python Scripting: Capable of integrating Python scripts for advanced visualizations within Power BI.
      • Data Modeling: Proficient in designing and maintaining robust data models to support analytical needs.
      • Row-Level Security: Knowledgeable in implementing row-level security to control access to data for different user roles.
      • Bookmarks: Expert in using bookmarks to create interactive experiences and enable visual selection.
      • Creating Measures and Quick Measures: Developing custom and quick measures to drive insights.
      • Creating Hierarchies: Structuring data hierarchies to support drill-down functionality.
      • Action Filters: Applying action filters to improve interactivity between visuals.
      • Syncing Slicers: Synchronizing slicers across visuals to ensure cohesive data exploration.

        My comprehensive knowledge and hands-on expertise ensure that I can effectively transform raw data into actionable insights, delivering maximum value through Power BI.
  • Looker Studio
    • Looker much like PowerBI from Microsoft, the UI and the features much like PowerBI, in Looker Studio I can use Blending, Field Calculation, Parameters, Filters, and many more..
  • Metabase
    • Metabase a litte difference from the tools mentioned above, in metabase I can create connections to databases, create questions for visualizations, drill-trrough, x-rays, breakout, custom expressions, join, multi-level aggregations, and many more..
  • Python (Matplotlib, Seaborn, etc)
    • When I use Python visualization, when I teach about machine learning, I primarily use Matplotlib and Seaborn for basic visualizations as I explore the data.

Analytics

  • Microsoft Excel
    • I can use Excel for many complex formulas, one of which is XLOOKUP and LET. XLOOKUP can help you search using an array, which allows you to search a column before searching, making it more flexible, like INDEX and MATCH. LET can help you assign variables to formulas, so when you want to create a complex formula, which will make you create repeated syntax in one formula, you can assign that syntax to a variable using LET.
      In Excel, I can use:
      • Pivot
      • All Visualizations / Visual Pivot
      • PowerQuery
      • Complex formulas
      • Simple macros
      • Advanced conditional formatting

        In Excel, I can create complex dashboards, or complex processes like this and this
  • Google Sheet
    • My proficient in google sheet is same as using Microsoft Excel, I can use advance formula and one thing I like from Google Sheet is using ARRAYFORMULA for creating formula when I need multiple filter or cluase, and IMPORTRANGE and QUERY when I need to import data from another sheet/table or from another file in my drive.
  • Statistical Methods
    • Every problem I want to solve, I use statistical methods to support my hypothesis, I also use many statistical methods based on the problem I want to solve, but mainly I use:
      • Descriptive Statistics such as:
        • Measures of Central Tendency, to summarize data.
        • Measures of Spread, to understand data variability.
        • Data Summary, for reporting on key metrics.
      • Also I’m using Inferential Statistics but with moderate usage, like using:
        • Hypothesis Testing, to make inference about data.
        • Regression Analysis, for identifying relationships.
        • Confidence Intervals, to estimate range ranges for projections.
        • P-value, for hypothesis testing.
      • Probability and Distributions, like Normal, Binomial/Poisson Distributions.
      • Advanced Statistics, such as ANOVA, Time Series Analysis, Multivariate Analysis.
  • SQL Query
    • I can use SQL in many databases, but mainly I’m using it in Microsoft SQL Server. I use SQL for retrieving data, but also I can create complex queries if I want to perform analysis in the query, like using Sub-queries, CTE table, Join, Grouping, Window, and many more.
      But if the problem is not to complex, I’m prefer using Microsoft Excel, and when I need to visualize the data, and the visualization to be complex, I’m prefer using Tableau or PowerBI.
  • Python (Pandas, Numpy, Scipy, etc)
    • I use analysis in python when the data is hard to clean, or the size is too big, so I will use Python, with libraries that will help me analyze the data, such as Pandas and Numpy which I use most often, and matplotlib or seaborn to visualize the data. I mainly use Jupyter Notebook in Google Colabs, because I don’t have to think too much about where the data is stored, because the data is stored in my Google Drive. And where my jupyter notebook or scripts are stored on my laptop.
Data Science

Machine Learning

  • Supervised Learning
    • I can solve Regression and Classification problems using Python, mainly I use Scikit-learn to model my data. I understand different types of Regression algorithms such as Linear, Logistic, Polynomial, Elastic Net, Lasso, and many more, to solve regression problems, and also different types of classification algorithms such as Decision Tree, Random Forest, Support Vector Machine (SVM), Naive Bayes, k-Nearest Neighbors, and many more.
  • Unsupervised Learning
    • I understand unsupervised learning like clustering, I can use K-Means and Fuzzy C-Means for clustering for Quantitative Problem, and solve Categorical clustering using K-Modes and K-Prototype.
  • Scikit-learn
    • This library is simple and have many algorithms/tools that I need for solving machine learning problems, such as spliting the data to data train and test, preprocessing, model evaluation and many more.
  • Applied Math
    • I have a moderate proficiency in applied mathematics, with a solid foundation in mathematical concepts and techniques. I can effectively solve standard numerical or analytical problems and apply mathematical models to real-world situations. My skills include performing calculations, deriving solutions for practical scenarios, and working with tools like algebra, calculus, and numerical methods.
      While I am confident in many areas, I recognize there’s room to grow, particularly in mastering advanced techniques, tackling complex modeling, or diving deeper into specialized applications.
  • Data Modeling & Evaluation
    • I can create model based on the problems that I need to solve, like regression, classification, clustering, and choose the best evaluation model for specific models.
  • Python
    • When creating machine learning problems, I’m using python for exploring and creating models.

Deep Learning

  • Tensorflow & Keras [certificate]
    • I have a moderate proficiency in TensorFlow and Keras, giving me a solid understanding of building and training machine learning models. I am comfortable with implementing standard workflows such as data preprocessing, designing neural network architectures, and optimizing models for performance.

      While I can confidently handle many typical tasks, I see opportunities to deepen my expertise in advanced techniques, fine-tuning large models, and tackling complex real-world projects.

      I use sequential models for solving complex predictions problems using Keras, and I can use Tensorflow if I need solving something that hard using sequentials problems, like creating system recommendations models.
  • Computer Vision
    • I have a moderate proficiency in solving computer vision problems, with experience working on tasks like image classification and object tracking. I am capable of using pre-trained models, designing custom pipelines, and applying standard techniques to address a range of challenges in this domain.

      While I have a solid foundation, I recognize there’s room to enhance my skills, particularly in developing advanced solutions, optimizing performance, and tackling more complex computer vision applications.
  • Natural Language Processing (NLP)
    • I would describe my skills in natural language processing (NLP) as strong. I have a solid understanding of text classification techniques and a good grasp of working with large language models (LLMs). My experience includes leveraging LLMs for tasks such as sentiment analysis, topic modeling, and summarization. I am comfortable implementing solutions with state-of-the-art NLP frameworks and have a good balance of theoretical knowledge and practical application. While there’s room for growth in fine-tuning advanced models and tackling highly complex NLP problems, I feel confident in solving most text-related challenges effectively.
  • Time Series (RNN – LSTM)
    • I have intermediate skills in time series problems. I have some experience working with techniques like LSTMs for modeling and forecasting, but there’s room for growth in terms of advanced methods and optimization strategies
  • Deployment
    • I can deploy machine learning problems and create pipelines, when using Tensorflow I can deploy to TF-Lite when deplying to mobile applications, Tensorflow.js when deploying to web applications, and I can use TF-Serving. Also I can create API for machine learning models.
Data Engineer

Databases

  • Microsoft SQL Server
    • Managing data in Microsoft SQL Server is like any others databases, but I have more time using SQL Server from any other databases, I’m familiar with the UI and with many features.
      I can use some features for specific task, such as:
      • SQL Server Profiler, for profiling, monitoring and tuning the database with recommendations about creating Index and Statistics. Also I can complete this task using SQL Trace using stored procedure.
      • Monitoring Tools in Computer Mangement, for monitoring performance in database, such as memory, locks, plan cache, processor time, transactions and many more.
      • Data Quality Services (DQS), I use this for cleaning data, like identifying duplicates, missing values, typos, and many more.
      • Master Data Services (MDS), for creating master data from database and use that in many difference services to make it consistences.
      • SQL Server Agent, for creating automation like job, alert, and notification schedule for many kind of task in databases, and for creating schedule for ETL that I create using SSIS.
      • Server Audit, for creating procedure or alert for data access.
      • Backup and Restore Task, I understand implementation in backup strategy such as full backup, partial backup, T-Log backup, and any others backup methods for difference task.
      • Maintenance Plan, for creating automations for any maintenance task, such as rebuild index, statistics, create backups, and many more.
      • Managing Storage, I understand types of storage and how to use them like mdf, ndf, and ldf. Also I understand filegroups for separating data in database, and why we need to use that.
      • Any others administrative tools and task, like:
        • Create and manage mirroring or replications.
        • Import and export data, using SQL Server Import Export wizard, BCP, BULK INSERT and OPENROWSET.
        • Managing SQL Server Security, from servel-level and database-level.
  • Data Warehousing using SQL Server
    • I understand data warehouse architecture, and how to implement that in Micorosft SQL Server, from creating the database that support data warehouse, create staging database when the data warehouse is complex and huge.
      I understand and I can create data warehouse in SQL Server, I need SSIS as ETL Tools for transfering and manipulating data, creating Master Data in Master Data Services (MDS) and Data Quality Services (DQS) for supporting the data warehouse, implementing ETL jobs in SQL Server Agent, and consuming data warehouse to create OLAP or create dashboard in many different BI tools.
  • MySQL
    • I have a solid working experience with MySQL Over time, I’ve gained proficiency in administering and tuning MySQL databases to ensure optimal performance and reliability. I’m comfortable with tasks like database installation, configuration, and management. I handle user permissions and roles, perform regular backups, and manage replication for high availability. In terms of database tuning, I’ve worked with query optimization, indexing, and adjusting MySQL parameters to improve performance. I frequently monitor slow query logs to identify performance bottlenecks and make improvements by creating appropriate indexes or rewriting inefficient queries. Additionally, I have experience with optimizing database schema design, analyzing query execution plans, and utilizing tools like EXPLAIN to fine-tune queries.

      I’ve also worked on configuring MySQL’s memory usage, buffer pools, and cache settings to ensure the database operates efficiently even under heavy load. Furthermore, I have experience with partitioning tables and setting up replication for both read-write and read-only replicas to improve database scalability and fault tolerance. Overall, while I’m confident in my abilities to administer and tune MySQL databases, I continue to deepen my knowledge to stay up-to-date with best practices and new features.
  • Oracle
    • I have experience using Oracle databases, primarily focused on administering and tuning the databases. In terms of administration, I am comfortable with tasks such as setting up user accounts, managing roles and permissions, and performing basic backup and recovery operations. I’ve worked with Oracle’s tools for monitoring database performance, and I’m familiar with configuring and managing instances, tablespaces, and schemas.

      While my experience with Oracle is still growing, I am eager to deepen my understanding of advanced features such as partitioning, clustering, and more complex optimization techniques, as well as automating routine administrative tasks.
  • PostgreSQL
    • My experience with PostgreSQL is currently at a beginner level, roughly a 1 out of 5. I’m still learning the fundamentals of SQL and how to effectively interact with PostgreSQL databases.
      • However, I’m eager to expand my knowledge and am particularly interested in database administration. I’ve started to explore basic administrative tasks, such as:
      • Creating and managing users and roles: I’ve learned how to create new users, assign them appropriate privileges, and manage their access to specific databases and tables.
      • Basic backup and recovery: I’ve begun to understand the importance of regular backups and have started exploring basic backup and recovery procedures.
      • Monitoring database performance: I’m learning to monitor key performance indicators (KPIs) such as resource utilization (CPU, memory, disk I/O) and query execution times to identify potential bottlenecks.
      • Basic troubleshooting: I’m developing the ability to diagnose and resolve common database issues, such as connection problems and simple query errors.
  • Microsoft Access
    • I can create simple database using access when needed and I can use access for different use cases.
  • Hadoop (HDFS, Hue, Hive & HBase)
    • I understand how to use Hadoop architecture and, like using HDFS, Hive and HBase for managing unstructural data.

Extract, Transfer, Load (ETL)

  • Pentaho Data Integration
    • I have significant experience working with Pentaho Data Integration (PDI) and Pentaho Server. I am proficient in various transformation steps within PDI, such as:
      • Lookup: Joining data from different sources based on a common key.
      • Create New Column: Generating new fields based on existing data, calculations, or constants.
      • Data Conversion: Transforming data types (e.g., string to date, integer to decimal).
      • Filtering: Selecting specific rows based on conditions.
      • Aggregation: Summarizing data, such as calculating sums, averages, and counts.
      • Scripting: Using scripting languages (like JavaScript) for complex data manipulation.

        I have a solid understanding of the Pentaho architecture, includin
      • Spoon: The graphical user interface for designing and developing ETL jobs.
      • Kitchen: The command-line tool for executing jobs and transformations.
      • Carte: The server component that manages and executes jobs on a distributed environment.
      • Pentaho Server: The central hub for managing and monitoring ETL processes, scheduling jobs, and accessing reports.

        I am comfortable with:
      • Deploying and scheduling jobs on the server.
      • Monitoring job executions and troubleshooting issues.
      • Configuring server settings and user permissions.
      • Basic administration tasks, such as managing repositories and monitoring server performance.

        I am eager to further enhance my skills in Pentaho Server administration, particularly in areas such as performance tuning, advanced scheduling, and integrating with other enterprise systems.
  • Microsoft SSIS
    • I possess a strong foundation in SSIS, evidenced by my ability to effectively design and implement complex ETL processes. My skillset encompasses:
      • Package Development: I can proficiently create and manage SSIS packages, projects, and components, ensuring efficient data movement and transformation.
      • Data Flow Mastery: I excel in optimizing data flow performance through techniques like data partitioning, caching, and utilizing efficient transformations. I am adept at implementing various data flow components, including transformations for data cleaning, manipulation, and aggregation.
      • Control Flow Management: I effectively implement control flow within SSIS packages using tasks, containers, and precedence constraints to orchestrate the execution order and handle contingencies.
      • Dynamic Package Creation: I can leverage variables, parameters, and expressions to create dynamic and adaptable SSIS packages that cater to varying business requirements.
      • Robustness and Reliability: I incorporate features like transactions, checkpoints, and debugging mechanisms to ensure the reliability and recoverability of SSIS packages.
      • Comprehensive Logging: I implement robust logging mechanisms to track package execution, identify errors, and monitor performance.
      • Incremental ETL: I can effectively implement incremental ETL processes using techniques like change data capture, change tracking, and time-based comparisons to efficiently extract and load only the modified data.
      • Lookup Transformation: I effectively utilize the Lookup transformation to enrich data by retrieving related information from other sources.

        Areas of Continued Growth
        While I possess a strong understanding of SSIS, I am continuously seeking opportunities to expand my expertise in:
      • Advanced Analytics: Integrating SSIS with machine learning and advanced analytics platforms.
      • Cloud Integration: Leveraging SSIS in cloud environments, such as Azure Data Factory.
      • Data Quality and Profiling: Implementing data quality checks and profiling techniques within SSIS packages.

        I am confident in my ability to contribute significantly to data integration projects and am eager to learn and grow further within the SSIS ecosystem.

Analytics

  • Microsoft SSAS
    • I have a solid foundation in SQL Server Reporting Services (SSRS). I’m proficient in building multidimensional databases, starting with creating data sources and views. I can effectively work with cubes and dimensions, including configuring dimensions, defining attribute hierarchies, and sorting and grouping attributes. I understand how to work with measures and measure groups, including adding calculations to cubes. I’m comfortable using Multidimensional Expressions (MDX) to query cubes and enhance their functionality. I have experience working with KPIs, actions, perspectives, and translations within the SSRS environment.

      I have also delved into implementing Analysis Services Tabular Data Model, where I can create and enhance tabular models using Data Analysis Expressions (DAX).
  • Microsoft SSRS
    • When it comes to SSRS report development, I’m skilled in creating reports using the Report Designer. I can effectively group and aggregate data, publish and view reports, and present data graphically. I’m also proficient in filtering reports using parameters.
  • Spark
    • My exposure to Apache Spark is currently limited. I have begun to explore its foundational concepts, such as distributed computing and resilient distributed datasets (RDDs). I understand the basic idea of using Spark for large-scale data processing and analysis. However, my practical experience with Spark is minimal. I have not yet gained proficiency in writing Spark applications, utilizing common libraries like Spark SQL and Spark MLlib, or optimizing Spark jobs for performance. I am highly motivated to learn and grow my skills in Spark, and I am actively seeking opportunities to gain practical experience through projects and tutorials.
Others

Managements

  • Data Management [certificate]
    • I have a comprehensive understanding of all frameworks within DMBOK v2, and my expertise spans a wide range of areas within data management. Below is a detailed breakdown of my experience and strengths:
      • DMBOK v2 Frameworks Expertise
        I have an in-depth understanding of the following frameworks within DMBOK v2:
        • Data Governance: Knowledge of setting policies, standards, and processes to manage and protect data assets.
        • Data Architecture: Proficient in designing and implementing data systems that align with organizational needs.
        • Data Modeling and Design: Skilled in developing data models and schemas to structure data for optimal use.
        • Data Storage and Operations: Familiar with storage strategies and operational processes for data management.
        • Data Security: Experienced in securing data assets against unauthorized access and breaches.
        • Data Integration and Interoperability: Strong in combining data from multiple sources to ensure seamless interaction.
        • Document and Content Management: Knowledgeable in managing unstructured data, documents, and content repositories.
        • Reference and Master Data Management: Proficient in maintaining consistent and accurate reference and master data.
        • Data Warehousing and Business Intelligence: Expert in designing, building, and utilizing data warehouses for analytics.
        • Metadata Management: Skilled in capturing and maintaining metadata to ensure data transparency.
        • Data Quality: Experienced in ensuring data accuracy, consistency, and reliability.
        • Big Data and Data Science: Strong background in handling and analyzing large data sets to derive actionable insights.
        • Data Handling Ethics: Familiar with ethical considerations in data management, including privacy and compliance.
      • Strengths in Key Areas
        My core strengths are in:
        • Data Warehousing and Business Intelligence: Designing and implementing systems that enable advanced analytics and reporting.
        • Big Data and Data Science: Leveraging large-scale data to generate insights and support decision-making processes.
      • Certification
        I have earned the CDMP (Certified Data Management Professional) Data Management Fundamentals Practitioner Level certification, showcasing my strong foundational knowledge and practical skills in data management.

        This combination of knowledge, strengths, and certification highlights my capability to contribute meaningfully to data management initiatives and projects.
  • Project Management
    • I have a solid understanding of project management principles as outlined in PMBOK v7, which equips me with the knowledge to effectively manage and contribute to diverse projects. Below is a detailed summary of my expertise and approach:

      Comprehensive Knowledge of PMBOK v7 Domains
      I have a thorough understanding of the eight performance domains and associated frameworks outlined in PMBOK v7:
      • Stakeholder Engagement:
        Skilled at identifying and analyzing stakeholders, understanding their needs, and maintaining active engagement throughout the project lifecycle.
      • Team Performance:
        Familiar with fostering collaboration, building high-performing teams, and managing team dynamics to achieve project objectives.
      • Development Approach and Life Cycle:
        Knowledgeable in selecting and tailoring development approaches (predictive, agile, or hybrid) to align with project requirements and organizational goals.
      • Planning:
        Experienced in creating comprehensive plans that address scope, schedule, cost, resources, and risks while ensuring alignment with strategic objectives.
      • Project Work:
        Capable of managing project execution, monitoring progress, and ensuring deliverables meet quality standards and stakeholder expectations.
      • Delivery:
        Focused on delivering value by prioritizing outputs and outcomes that align with organizational goals and project objectives.
      • Measurement:
        Proficient in using metrics, KPIs, and other measurement tools to assess project performance and drive informed decision-making.
      • Uncertainty and Risk Management:
        Strong in identifying, analyzing, and responding to uncertainties, ensuring that risks are mitigated effectively.

        Familiarity with Tailoring Concepts
        I understand the importance of tailoring project management practices to suit the specific context, scale, and complexity of a project, ensuring that all processes remain relevant and effective.

        Integration of Principles and Frameworks
        I align my approach to the 12 principles of project management from PMBOK v7, such as stewardship, collaboration, value delivery, and adaptability, ensuring projects are executed with a balance of strategy and flexibility.

        Commitment to Growth
        I am dedicated to improving my project management skills further by refining my application of PMBOK v7 methodologies and pursuing opportunities to manage complex projects that demand a nuanced understanding of these domains.