This document summarizes Hong-Bing Li's portfolio of business intelligence projects using Microsoft BI tools. It includes 3 SQL Server Reporting Services reports, 8 dashboards in SharePoint including scorecards and KPIs, 18 examples of SQL programming, and 25 SQL Server Integration Services packages for data integration. The document provides detailed descriptions and screenshots of sample reports, dashboards, SQL code, and SSIS packages developed by the author.
This presentation "Tableau interview questions and answers" will help you to get prepared for Tableau job interviews. Tableau has become a mission-critical data visualization tool that helps people quickly understand data. The usefulness and popularity of Tableau make it a necessary skill for anyone working with data. As a reflection of the growing importance of data and tools for understanding it, the number of jobs requiring Tableau skills has increased dramatically since 2014.If you’re moving into the field of data analytics or you’re moving up the ladder and need Tableau skills, you’ll probably be interviewing for a job someday soon. We’re here to help, with the key Tableau job interview questions along with their best answers for you to think about ahead of time.
Some of the Tableau interview questions discussed in this presentation are mentioned below. Click on the time stamps to directly jump to that particular question.
1. What are the datatypes supported in Tableau?
2. What do you understand by dimensions and measures?
3. What do you understand by Discrete and Continuous in Tableau?
4. What are filters? Name the different filters in Tableau.
5. There are three customer segments in the Superstore dataset. What percent of the total profits is associated with the Corporate segment?
6. What are the different joins in Tableau? Give example
7. What is the difference between Join and Blending?
8. What is the difference b/w Live and Extract?
9. What is a Calculated Field? How will you create one?
10. How can you display top five and last five sales in the same view ?
11. Is there any difference between Sets and Groups, in Tableau?
12. What is a Parameter in Tableau? Give an example.
13. What is the difference between Tree maps and Heat maps?
14. What is the difference b/w .twbx and .twb?
15. Explain the difference b/w Tableau worksheet, dashboard, story, and workbook?
16. What do you understand by Blended Axis?
17. What is the use of dual axis? How do you create one?
18. What will the following function return? - Left(3, “Tableau”)
19. How do you handle Null and other special values?
20. Find the top product subcategories by Sales within each delivery method. Which sub-category is ranked #2 for first class ship mode?
21. Find the customer with the lowest overall profit. What is his/her profit ratio?
22. What is the Rank function in Tableau?
23. How can you embed a webpage in a dashboard?
24. Design a view to show region wise profit and sales?
25. How can you optimize the performance of a dashboard?
26. Which visualization will be used in the given scenarios:
27. What will you do if some country/province (any geographical entity) is missing and displaying a null when you use map view?
28. What is LOD expression?
29. How can you calculate daily profit measure using LOD?
30. How can you schedule a workbook in Tableau after publishing it?
Learn more at: https://www.simplilearn.com/
Tableau software is a basic requirement for any business to gain insight into the development of the company. It allows any non-technical user to easily create or develop the customized dashboards that facilitate insight into a broad spectrum of information. It is a must know interactive business intelligence tool in the field of data visualization.
MSBI online training offered by Quontra Solutions with special features having Extensive Training will be in both MSBI Online Training and Placement. We help you in resume preparation and conducting Mock Interviews.
Emphasis is given on important topics that were required and mostly used in real time projects. Quontra Solutions is an Online Training Leader when it comes to high-end effective and efficient IT Training. We have always been and still are focusing on the key aspect which is providing utmost effective and competent training to both students and professionals who are eager to enrich their technical skills.
This presentation "Tableau interview questions and answers" will help you to get prepared for Tableau job interviews. Tableau has become a mission-critical data visualization tool that helps people quickly understand data. The usefulness and popularity of Tableau make it a necessary skill for anyone working with data. As a reflection of the growing importance of data and tools for understanding it, the number of jobs requiring Tableau skills has increased dramatically since 2014.If you’re moving into the field of data analytics or you’re moving up the ladder and need Tableau skills, you’ll probably be interviewing for a job someday soon. We’re here to help, with the key Tableau job interview questions along with their best answers for you to think about ahead of time.
Some of the Tableau interview questions discussed in this presentation are mentioned below. Click on the time stamps to directly jump to that particular question.
1. What are the datatypes supported in Tableau?
2. What do you understand by dimensions and measures?
3. What do you understand by Discrete and Continuous in Tableau?
4. What are filters? Name the different filters in Tableau.
5. There are three customer segments in the Superstore dataset. What percent of the total profits is associated with the Corporate segment?
6. What are the different joins in Tableau? Give example
7. What is the difference between Join and Blending?
8. What is the difference b/w Live and Extract?
9. What is a Calculated Field? How will you create one?
10. How can you display top five and last five sales in the same view ?
11. Is there any difference between Sets and Groups, in Tableau?
12. What is a Parameter in Tableau? Give an example.
13. What is the difference between Tree maps and Heat maps?
14. What is the difference b/w .twbx and .twb?
15. Explain the difference b/w Tableau worksheet, dashboard, story, and workbook?
16. What do you understand by Blended Axis?
17. What is the use of dual axis? How do you create one?
18. What will the following function return? - Left(3, “Tableau”)
19. How do you handle Null and other special values?
20. Find the top product subcategories by Sales within each delivery method. Which sub-category is ranked #2 for first class ship mode?
21. Find the customer with the lowest overall profit. What is his/her profit ratio?
22. What is the Rank function in Tableau?
23. How can you embed a webpage in a dashboard?
24. Design a view to show region wise profit and sales?
25. How can you optimize the performance of a dashboard?
26. Which visualization will be used in the given scenarios:
27. What will you do if some country/province (any geographical entity) is missing and displaying a null when you use map view?
28. What is LOD expression?
29. How can you calculate daily profit measure using LOD?
30. How can you schedule a workbook in Tableau after publishing it?
Learn more at: https://www.simplilearn.com/
Tableau software is a basic requirement for any business to gain insight into the development of the company. It allows any non-technical user to easily create or develop the customized dashboards that facilitate insight into a broad spectrum of information. It is a must know interactive business intelligence tool in the field of data visualization.
MSBI online training offered by Quontra Solutions with special features having Extensive Training will be in both MSBI Online Training and Placement. We help you in resume preparation and conducting Mock Interviews.
Emphasis is given on important topics that were required and mostly used in real time projects. Quontra Solutions is an Online Training Leader when it comes to high-end effective and efficient IT Training. We have always been and still are focusing on the key aspect which is providing utmost effective and competent training to both students and professionals who are eager to enrich their technical skills.
This quick demo illustrates how I used a stored procedure with multiple selected parameter values within a SSRS Report. This technique can be used in the situation where developers want to utilize stored procedures, either by creating them from scratch or from existing legacy system, to develop new SSRS reports. It allows organizations to take advantage of the strength of stored procedures in maintenance and performance.
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
Show drafts
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
2. Slide Contents
3 Reports (SSRS)
8 Dashboard: Scorecard & KPI (SharePoint)
18 SQL Programming
25 Data Integration Services (SSIS)
This portfolio contains examples of my business intelligence
projects using Microsoft BI Product Stack.
7. 7
Whenever users make a selection on the "City" parameter, the cascading parameter "Product
SKU" is processed immediately. Its values are filtered dynamically based on two factors:
A. Selected cities B. Product SKU with dollar Sales greater than “0 “
The technique to implement cascading parameters in SSRS using MDX, which is based on OLAP,
is somewhat more complex than that using SQL, which is based on regular OLTP RDBMS.
9. 9
Large Scorecard with Multiple KPIs and their Hotlinks to a
supporting report (Part 1). Right click a KPI, a supporting chart or table will
pop up to the right of the Scorecard, as shown in the next two slides.
10. 10
Large Scorecard with Multiple KPIs and their Hotlinks to a supporting
report (Part 2 with partial Supporting Chart)
11. Large Scorecard with Multiple KPIs and their Hotlinks to a supporting
report (Part 3 with the complete Supporting Chart)
12. This dual Y-axis chart is a great tool for data analysis: 1. Two different types of measures
can be analyzed simultaneously against dimensional data on the X-Axis, such as Dollar
Sales (left Y-axis) and Product Percent of Parent Sales (right Y-Axis) shown below; 2. These
two measures can be broken out further to provide more detail in tables or charts (see
below) where the right Y-Axis measuring Product Percent is further explained by the Product
Siblings breakout; 3. Data can be explored at different levels of the Hierarchy family (see
the top Product Hierarchy dropdown list) which functions as a filter, allowing one to obtain
summary and detail statistics at different levels accordingly and export them to Excel or
PowerPoint; and 4. Data points in the chart can be drilled down to various dimensions
allowing for the creation of additional charts (see chart in next slide) which permit one to
investigate the contribution of various factors.
13. Continued: this chart is generated by drilling down from the
previous slide. For example, the 21.32% of health and fitness
sales of parents in Aug. 2005 is broken out by region.
17. 17
This is an example of a KPI developed from the AllWorks.cube, which is deployed to
the Excel Spreadsheet for the end users. All the data in the cube, including all KPIs,
can be explored through the Pivot Table Field List.
18. SQL Programming
SQL Programming covers a broad range of content: Data Types and
Variables, Specialized Functions, Stored Procedures, Control-Of-Flow Operations,
Error Handling, Etc. Due to time/space constraints, I will illustrate only some of
the relatively new SQL functions/procedures/ programs that I have used in my
projects in the following:
1. Data Modification: OUTPUT clause, MERGE, select TOP(with ties) option
2. Aggregation: RANK() OVER (Partition by), GROUPING SETS
3. SQL Functions: PIVOT, CROSS APPLY
4. Common Table Expression (CTE), Correlated and Recursive Queries
5. User Defined Functions (UDF) that returns TABLE type
6. Error Handling Routine:
Begin Try...End Try
Begin Catch...End Catch
26. A new database “All Works” is setup as the staging area for the ETL process. A
thorough understanding of the relationships between the tables in the data
diagram is important in determining the sequence of tables to be loaded and in
enforcing referential integrity.
26
27. A Script Task is utilized to maintain multiple sets of variables with scripts in C#, for
instance, one for keeping track of row counts of data processed dynamically at the
folder level, one for row counts at the file level.
28. One SSIS package is created to do ETL for one target table. The following illustrates
the data processing within the Job Timesheets package: the data process pipeline
starts by extracting data from a CSV file. The data is then conversed, processed and
transformed (filter, remove duplicates, lookups, validate) as it passes through the
pipeline, and is finally loaded into the target job timesheets table either as inserts
or updates. It logs any rows that error out for review and correction. Similarly,
seven more packages are generated for seven target tables.
28
29. 29
A Sequence Container is deployed to run the eight ETL packages in sequence based on the
relationships between the tables in the “All Works” Database to ensure referential integrity. If the
eight packages are processed successfully, data maintenance tasks are performed. A success or
failure notice email will be sent out depending on whether the data maintenance tasks are all
successfully completed or not.
A Master Package is created to contain the Sequence Container, the maintenance tasks and the
email notices; then a SQL Server Agent Job is setup to run the Master Package on a predefined
schedule to automate the entire data processing procedure.