ODSC - Open Data Science

JUNE 12, 2023

This article is an excerpt from the book Expert Data Modeling with Power BI, Third Edition by Soheil Bakhshi, a completely updated and revised edition of the bestselling guide to Power BI and data modeling. A quick search on the Internet provides multiple definitions by technology-leading companies such as IBM, Amazon, and Oracle.

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phData

MAY 6, 2025

Its functionality comprises standing as an intermediary between raw data and visualizations and, thereby, acts as the place to facilitate ease of data exploration and analysis. It represents a centralized, shared data definition, allowing aggregations and other transformations. Select Dataset from the dropdown menu.

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Mlearning.ai

JUNE 19, 2023

How you now anonymize Data more easily Photo by Dušan veverkolog on Unsplash Google has just announced the public preview of BigQuery differential privacy with SQL building blocks. You can use these functions to anonymize their data.

Data Lakes 52

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IBM Journey to AI blog

JULY 5, 2023

Another unexpected challenge was the introduction of Spark as a processing framework for big data. It gained rapid popularity given its support for data transformations, streaming and SQL. But it never co-existed amicably within existing data lake environments. Comprehensive data security and data governance (i.e.

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AWS Machine Learning Blog

SEPTEMBER 18, 2024

Additionally, Feast promotes feature reuse, so the time spent on data preparation is reduced greatly. It promotes a disciplined approach to data modeling, making it easier to ensure data quality and consistency across the ML pipelines. The following figure shows schema definition and model which reference it.

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IBM Journey to AI blog

JANUARY 10, 2023

This allows data that exists in cloud object storage to be easily combined with existing data warehouse data without data movement. The advantage to NPS clients is that they can store infrequently used data in a cost-effective manner without having to move that data into a physical data warehouse table.

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Dataconomy

APRIL 27, 2023

However, with the evolution of the internet, the definition of transaction has broadened to include all types of digital interactions and engagements between a business and its customers. The core definition of transactions in the context of OLTP systems remains primarily focused on economic or financial activities.

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Alation

JANUARY 17, 2023

The modern data stack is a combination of various software tools used to collect, process, and store data on a well-integrated cloud-based data platform. It is known to have benefits in handling data due to its robustness, speed, and scalability. A typical modern data stack consists of the following: A data warehouse.

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phData

AUGUST 22, 2024

Snowflake Cortex stood out as the ideal choice for powering the model due to its direct access to data, intuitive functionality, and exceptional performance in handling SQL tasks. Looking at the SQL code, it appears that CONTRACT_BREAK is hardcoded as a constant value ‘1’ in the final SELECT statement.

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Alation

MAY 24, 2022

Prime examples of this in the data catalog include: Trust Flags — Allow the data community to endorse, warn, and deprecate data to signal whether data can or can’t be used. Data Profiling — Statistics such as min, max, mean, and null can be applied to certain columns to understand its shape.

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phData

APRIL 13, 2023

Security – Administers Snowflake’s security, such as data encryption. Sharing and Collaboration – Manages how data is shared between Snowflake accounts. SQL Optimization – Processes the user-entered SQL queries to be run in Snowflake. Transactions – Ensures SQL queries are ACID compliant.

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IBM Journey to AI blog

JANUARY 18, 2023

They defined it as : “ A data lakehouse is a new, open data management architecture that combines the flexibility, cost-efficiency, and scale of data lakes with the data management and ACID transactions of data warehouses, enabling business intelligence (BI) and machine learning (ML) on all data. ”.

Data Lakes 52

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phData

JULY 18, 2023

With the birth of cloud data warehouses, data applications, and generative AI , processing large volumes of data faster and cheaper is more approachable and desired than ever. First up, let’s dive into the foundation of every Modern Data Stack, a cloud-based data warehouse.

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Pickl AI

AUGUST 1, 2023

The primary goal of Data Engineering is to transform raw data into a structured and usable format that can be easily accessed, analyzed, and interpreted by Data Scientists, analysts, and other stakeholders. Future of Data Engineering The Data Engineering market will expand from $18.2

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Pickl AI

JUNE 7, 2024

It is a process for moving and managing data from various sources to a central data warehouse. This process ensures that data is accurate, consistent, and usable for analysis and reporting. Definition and Explanation of the ETL Process ETL is a data integration method that combines data from multiple sources.

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Pickl AI

AUGUST 11, 2024

Consider factors such as data volume, query patterns, and hardware constraints. Document and Communicate Maintain thorough documentation of fact table designs, including definitions, calculations, and relationships. Establish data governance policies and processes to ensure consistency in definitions, calculations, and data sources.

Data Quality 52

Data Quality Data Warehouse Data Governance Analytics 52

phData

JUNE 27, 2023

Using SQL-centric transformations to model data to be deployed. dbt is also great for data lineage and documentation to empower business analysts to make informed decisions on their data. Data Ingestion with Fivetran Fivetran is used to move your source(s) into a centralized space for storage.

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phData

MAY 25, 2023

One of the easiest ways for Snowflake to achieve this is to have analytics solutions query their data warehouse in real-time (also known as DirectQuery). The June 2021 release of Power BI Desktop introduced Custom SQL queries to Snowflake in DirectQuery mode. This ensures the maximum amount of Snowflake consumption possible.

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Pickl AI

AUGUST 9, 2024

Document Hierarchy Structures Maintain thorough documentation of hierarchy designs, including definitions, relationships, and data sources. Retail Industry In a retail data warehouse , hierarchies can be used to organise product categories. Avoid excessive levels that may slow down query performance.

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AWS Machine Learning Blog

JUNE 25, 2024

In addition, the generative business intelligence (BI) capabilities of QuickSight allow you to ask questions about customer feedback using natural language, without the need to write SQL queries or learn a BI tool. The raw data is processed by an LLM using a preconfigured user prompt. The LLM generates output based on the user prompt.

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phData

MARCH 1, 2024

This process introduces considerable time and effort into the overall data ingestion workflow, delaying the availability of data to end consumers. Fortunately, the client has opted for Snowflake Data Cloud as their target data warehouse. Go back to the SQL worksheet and verify if the files exist.

Data Engineering 52

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Pickl AI

JULY 14, 2024

Regarding retrieval, DBMS utilises query languages like SQL to retrieve information swiftly and accurately based on user requests. Moreover, DBMS systems manage data through functionalities such as indexing, which enhances retrieval speed by logically organising data. Best Data Engineering and SQL Books for Beginners.

Database 52

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Pickl AI

JULY 8, 2024

These pipelines automate collecting, transforming, and delivering data, crucial for informed decision-making and operational efficiency across industries. Organisations leverage diverse methods to gather data, including: Direct Data Capture: Real-time collection from sensors, devices, or web services.

Data Pipeline 52

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Snorkel AI

JUNE 27, 2023

First, you generate predictions and you store them in a data warehouse. So what that means is that when we write feature definitions, instead of writing them in Python, we write the feature for the online prediction process. So we write a SQL definition. So we need to access fresh data.

AI 52

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Mlearning.ai

JULY 10, 2023

To create a Scheduled Query, the initial step is to ensure your SQL is accurately entered in the Query Editor. A user-defined function (UDF) lets the user create a function by using a SQL expression or JavaScript code. These functions can then be used in your SQL queries in BQ to simplify and optimize your analysis.

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Alation

AUGUST 30, 2022

These range from data sources , including SaaS applications like Salesforce; ELT like Fivetran; cloud data warehouses like Snowflake; and data science and BI tools like Tableau. This expansive map of tools constitutes today’s modern data stack. We are starting with personalized homepages.

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Snorkel AI

JUNE 27, 2023

First, you generate predictions and you store them in a data warehouse. So what that means is that when we write feature definitions, instead of writing them in Python, we write the feature for the online prediction process. So we write a SQL definition. So we need to access fresh data.

AI 52

AI AI Data Warehouse Machine Learning 52

Snorkel AI

JUNE 27, 2023

First, you generate predictions and you store them in a data warehouse. So what that means is that when we write feature definitions, instead of writing them in Python, we write the feature for the online prediction process. So we write a SQL definition. So we need to access fresh data.

AI 52

AI AI Data Warehouse Machine Learning 52

Alation

JANUARY 25, 2022

Data fabric is now on the minds of most data management leaders. In our previous blog, Data Mesh vs. Data Fabric: A Love Story , we defined data fabric and outlined its uses and motivations. The data catalog is a foundational layer of the data fabric. ” 1.

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phData

JUNE 3, 2024

Taking it one step further, if you don’t want your data traversing the public internet, you can implement one of the private connections available from the cloud provider your Snowflake account is created on, i.e., Azure Private Link, AWS Privatelink, or Google Cloud Service Private Connect. Snowflake has you covered with Cortex.

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Machine Learning Machine Learning Database Cloud Data 52

phData

SEPTEMBER 5, 2023

Overall, these powerful cloud-based tools provide a scalable and cost-effective solution for managing, processing, and analyzing large volumes of data from Google Analytics in Snowflake. Need help setting up a data ingestion pipeline? It provides a fully managed data warehouse as a service.

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Flipboard

MARCH 21, 2025

Traditionally, answering this question would involve multiple data exports, complex extract, transform, and load (ETL) processes, and careful data synchronization across systems. The existing Data Catalog becomes the Default catalog (identified by the AWS account number) and is readily available in SageMaker Lakehouse.

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phData

OCTOBER 25, 2024

Data Quality Monitoring implements quality checks in operational data processes to ensure that the data meets pre-defined standards and business rules. This results in poor credibility and data consistency after some time, leading businesses to mistrust the data pipelines and processes.

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phData

MAY 6, 2024

Now, a single customer might use multiple emails or phone numbers, but matching in this way provides a precise definition that could significantly reduce or even eliminate the risk of accidentally associating the actions of multiple customers with one identity.

Data Lakes 52

Data Lakes Data Warehouse Cloud Data SQL 52

phData

NOVEMBER 13, 2023

Sidebar Navigation: Provides a catalog sidebar for browsing resources by type, package, file tree, or database schema, reflecting the structure of both dbt projects and the data platform. Efficient Data Retrieval: Quick access to metric datasets from your data platform is made possible by MetricFlow’s optimized processes.

Database 52

Database Business Intelligence Business Intelligence Data Silos 52

Alation

APRIL 14, 2022

Data pipeline orchestration. Support for languages and SQL. Moving/integrating data in the cloud/data exploration and quality assessment. Similar to a data warehouse schema, this prep tool automates the development of the recipe to match. It’s not a simple definition. Collaboration and governance.

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Data Governance ML ML Cloud Data 59

phData

AUGUST 15, 2023

dbt Labs is a robust platform that allows individuals comfortable with SQL to incorporate software engineering’s best practices into their data transformation pipelines. To do this, you’ll need to create a free dbt account , a Snowflake trial account (or another Data Warehouse), and a GitHub account.

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