Pickl AI

FEBRUARY 20, 2025

Gather, validate, and document business requirements. Both roles require strong analytical skills, proficiency in SQL and other programming languages, and the ability to interpret data and provide insights. Data Analysis: Proficiency in data analysis tools and techniques such as SQL, Excel, and data visualisation tools (e.g.,

Data Analyst 52

Data Analyst Data Analysis Data Analysis SQL 52

phData

OCTOBER 24, 2024

BI Tool Integration: A new dbt Semantic Layer connection to Power BI is coming soon! Again, for the category, we have two major announcements: Visual Low-Code Editor: An intuitive, visual drag-and-drop interface (currently in private beta) that allows you to create dbt models without writing SQL.

SQL 52

SQL Tableau Power BI Database 52

ODSC - Open Data Science

APRIL 26, 2023

Because they are the most likely to communicate data insights, they’ll also need to know SQL, and visualization tools such as Power BI and Tableau as well. Some of the tools you can expect to see used will be Power BI and Tableau Data Architect Before you ask, yes a data architect and a data engineer are quite different.

Data Analyst 52

Data Analyst Machine Learning Machine Learning Power BI 52

Pickl AI

AUGUST 9, 2024

Document Hierarchy Structures Maintain thorough documentation of hierarchy designs, including definitions, relationships, and data sources. This documentation is invaluable for future reference and modifications. Simplify hierarchies where possible and provide clear documentation to help users understand the structure.

Data Warehouse 52

Data Warehouse Data Quality ETL Business Intelligence 52

phData

MARCH 27, 2024

In the case of practice tests and quizzes, find the relevant section within Snowflake’s documentation for each question. The Snowpark playlist , in particular, is an invaluable source for learning about Snowpark: Snowflake’s set of libraries and runtimes that securely deploy and process non-SQL code.

Data Analyst 52

Data Analyst Data Engineer Data Engineering Data Engineering 52

phData

DECEMBER 4, 2023

The software you might use OAuth with includes: Tableau Power BI Sigma Computing If so, you will need an OAuth provider like Okta, Microsoft Azure AD, Ping Identity PingFederate, or a Custom OAuth 2.0 For greater detail, see the Snowflake documentation. And once again, for loading data, do not use SQL Inserts.

Clustering 98

Clustering Database SQL Data Pipeline 98

AWS Machine Learning Blog

MARCH 8, 2023

Marubeni’s internal models are based on Long Short-Term Memory (LSTM) architectures, which are well documented and easy to implement and customize in TensorFlow. Amazon Athena to provide developers and business analysts SQL access to the generated data for analysis and troubleshooting.

AWS 100

AWS Machine Learning Machine Learning Analytics 100

Pickl AI

JULY 28, 2023

Clean and Prepare Data: Ensure that your datasets are clean, well-organized, and properly documented. Python, R, SQL), any libraries or frameworks, and data manipulation techniques employed. You can enormously take up SQL Projects for Data Analyst portfolio showcasing your skills.

Data Analyst 52

Data Analyst Data Analysis Data Analysis Data Visualization 52

Pickl AI

DECEMBER 4, 2024

Grasp the Fundamentals of Data Analysis and Management Build a strong foundation in Data Analysis by learning data manipulation techniques using SQL and Excel. Focus on Python and R for Data Analysis, along with SQL for database management. This foundational knowledge is essential for any Data Science project.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Pickl AI

JULY 12, 2023

SQL (Structured Query Language) SQL is a standard language for managing relational databases. Also, it provides powerful commands for querying, filtering, sorting, and aggregating data. SQL is commonly used for data manipulation tasks, especially with structured datasets.

Data Analysis 52

Data Analysis Data Analysis Database Clean Data 52

phData

JUNE 20, 2024

What technology or platform can meet the needs of the business, from basic report creation to complex document analysis to machine learning workflows? One such feature is Document AI. This new feature enables the processing and extracting of data from documents in various formats and structures.

Data Governance 52

Data Governance Analytics Analytics Power BI 52

Pickl AI

JANUARY 28, 2025

documents and images). Common tools used in Business Intelligence architecture include ETL tools like Talend or Informatica for data integration, Tableau or Power BI for visualization, and SQL databases for storage. Data can be structured (e.g., databases), semi-structured (e.g., XML files), or unstructured (e.g.,

Business Intelligence 52

Business Intelligence Business Intelligence ETL Data Lakes 52

Pickl AI

SEPTEMBER 5, 2024

You should be skilled in programming languages such as Python, R, or SQL , which are commonly used for data manipulation and analysis. Azure Synapse Analytics Previously known as Azure SQL Data Warehouse , Azure Synapse Analytics offers a limitless analytics service that combines big data and data warehousing.

Azure 52

Azure Data Scientist Data Science Machine Learning 52

Pickl AI

APRIL 2, 2024

Unstructured Data: Data without a predefined structure, like text documents, social media posts, or images. SQL (Structured Query Language): Language for managing and querying relational databases. Tableau/Power BI: Visualization tools for creating interactive and informative data visualizations.

Data Science 52

Data Science Machine Learning Machine Learning Predictive Analytics 52

Pickl AI

AUGUST 11, 2024

Document and Communicate Maintain thorough documentation of fact table designs, including definitions, calculations, and relationships. Consider factors such as data volume, query patterns, and hardware constraints. Use indexing and partitioning strategies to improve query performance.

Data Quality 52

Data Quality Data Warehouse Data Governance Analytics 52

ODSC - Open Data Science

JANUARY 7, 2025

While knowing Python, R, and SQL is expected, youll need to go beyond that. Classification techniques, such as image recognition and document categorization, remain essential for a wide range of industries. Employers arent just looking for people who can program.

Data Scientist 40

Data Scientist Data Science Machine Learning Machine Learning 40

Alation

JANUARY 17, 2023

A legacy data stack usually refers to the traditional relational database management system (RDBMS), which uses a structured query language (SQL) to store and process data. SQL, however, remains a popular query language for both legacy and modern data stacks. Examples of BI tools include Looker, Power BI , and Tableau.

Data Warehouse 52

Data Warehouse ETL Tableau Cloud Data 52

Pickl AI

JULY 18, 2024

Unlike traditional relational databases, MongoDB stores data in flexible, JSON-like documents, allowing for dynamic schemas. Critical features of MongoDB include: Horizontal scalability, High availability through replica sets and A powerful aggregation framework that supports complex queries and data transformations. What Is MongoDB?

Database 52

Database SQL Data Analyst Database Administration 52

phData

MARCH 7, 2025

Copilot automates those repetitive tasks, like writing DAX queries or creating Power BI visuals, so that you can focus on the big picture. Accelerate Learning: Fabric is a powerful platform with a steep learning curve. Power BI: Creating visualizations in Power BI can be time-consuming.

Power BI 52

Power BI SQL Data Engineering Data Engineer 52

Pickl AI

MARCH 19, 2025

Tools like Python, SQL, Apache Spark, and Snowflake help engineers automate workflows and improve efficiency. Python, SQL, and Apache Spark are essential for data engineering workflows. SQL Structured Query Language ( SQL ) is a fundamental skill for data engineers.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52