ODSC - Open Data Science

FEBRUARY 6, 2024

This open-source streaming platform enables the handling of high-throughput data feeds, ensuring that data pipelines are efficient, reliable, and capable of handling massive volumes of data in real-time. Each platform offers unique features and benefits, making it vital for data engineers to understand their differences.

Data Engineer 52

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phData

SEPTEMBER 5, 2023

Google Analytics 4 (GA4) is a powerful tool for collecting and analyzing website and app data that many businesses rely heavily on to make informed business decisions. However, there might be instances where you need to migrate the raw event data from GA4 to Snowflake for more in-depth analysis and business intelligence purposes.

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phData

FEBRUARY 3, 2023

More and more businesses are looking to better leverage their outsourced call center data to make more data-driven decisions. To do this on your own, you would need to create a data warehouse, optimize the reporting performance, and very clearly visualize the data. Another way to think of it is as Data Activation.

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Alation

APRIL 14, 2023

People were familiar with the value of a data catalog (and the growing need for data governance ), though many admitted to being somewhat behind on their journeys. In this blog, I’ll share a quick high-level overview of the event, with an eye to core themes. In “The modern data stack is dead, long live the modern data stack!”

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Pickl AI

JULY 25, 2024

Must Read Blogs: Exploring the Power of Data Warehouse Functionality. Data Lakes Vs. Data Warehouse: Its significance and relevance in the data world. Exploring Differences: Database vs Data Warehouse. It is commonly used in data warehouses for business analytics and reporting.

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Mlearning.ai

FEBRUARY 16, 2023

The ultimate need for vast storage spaces manifests in data warehouses: specialized systems that aggregate data coming from numerous sources for centralized management and consistency. In this article, you’ll discover what a Snowflake data warehouse is, its pros and cons, and how to employ it efficiently.

Data Warehouse 52

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phData

DECEMBER 12, 2023

We are going to break down what we know about Victory Vicky based on all the data sources we have moved into our data warehouse. The loyalty program is located in the MarTech Stack and moves data effortlessly into the data warehouse. This information is also funneled into the data warehouse.

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ODSC - Open Data Science

FEBRUARY 15, 2024

These systems represent data as knowledge graphs and implement graph traversal algorithms to help find content in massive datasets. These systems are not only useful for a wide range of industries, they are fun for data engineers to work on. Interested in attending an ODSC event? Learn more about our upcoming events here.

Data Engineer 52

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Pickl AI

JULY 30, 2024

Flow-Based Programming : NiFi employs a flow-based programming model, allowing users to create complex data flows using simple drag-and-drop operations. This visual representation simplifies the design and management of data pipelines. Provenance Repository : This repository records all provenance events related to FlowFiles.

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ODSC - Open Data Science

JANUARY 18, 2024

Data engineers will also work with data scientists to design and implement data pipelines; ensuring steady flows and minimal issues for data teams. They’ll also work with software engineers to ensure that the data infrastructure is scalable and reliable. Interested in attending an ODSC event?

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

Dataversity

APRIL 30, 2021

The goal of digital transformation remains the same as ever – to become more data-driven. We have learned how to gain a competitive advantage by capturing business events in data. Events are data snap-shots of complex activity sourced from the web, customer systems, ERP transactions, social media, […].

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Precisely

MAY 13, 2024

Wide support for enterprise-grade sources and targets Large organizations with complex IT landscapes must have the capability to easily connect to a wide variety of data sources. Whether it’s a cloud data warehouse or a mainframe, look for vendors who have a wide range of capabilities that can adapt to your changing needs.

Data Governance 52

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phData

SEPTEMBER 27, 2024

Methods that allow our customer data models to be as dynamic and flexible as the customers they represent. In this guide, we will explore concepts like transitional modeling for customer profiles, the power of event logs for customer behavior, persistent staging for raw customer data, real-time customer data capture, and much more.

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Data Modeling Data Models Apache Kafka Data Lakes 52

IBM Journey to AI blog

OCTOBER 16, 2023

Curated foundation models, such as those created by IBM or Microsoft, help enterprises scale and accelerate the use and impact of the most advanced AI capabilities using trusted data. In addition to natural language, models are trained on various modalities, such as code, time-series, tabular, geospatial and IT events data.

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ODSC - Open Data Science

APRIL 4, 2024

Find out how to weave data reliability and quality checks into the execution of your data pipelines and more. Announcing the ODSC East 2024 Complete Schedule Check out this article for a full rundown of what you can expect from the ODSC East 2024 schedule, including keynotes, bootcamp sessions, extra events, and more.

Data Visualization 52

Data Visualization Analytics Analytics Big Data Analytics 52

phData

FEBRUARY 14, 2023

Data integration is essentially the Extract and Load portion of the Extract, Load, and Transform (ELT) process. Data ingestion involves connecting your data sources, including databases, flat files, streaming data, etc, to your data warehouse. Snowflake provides native ways for data ingestion.

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phData

OCTOBER 17, 2024

The DAGs can then be scheduled to run at specific intervals or triggered when an event occurs. It even offers a user-friendly interface to visualize the pipelines and monitor progress. The Data Source Tool can automate scanning DDL and profiling tables between source and target, comparing them, and then reporting findings.

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phData

OCTOBER 25, 2024

It’s common to have terabytes of data in most data warehouses, data quality monitoring is often challenging and cost-intensive due to dependencies on multiple tools and eventually ignored. To assign the DMF to the table, we must first add a data metric schedule to the table CUSTOMERS.

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phData

JANUARY 24, 2024

Fivetran includes features like data movement, transformations, robust security, and compatibility with third-party tools like DBT, Airflow, Atlan, and more. Its seamless integration with popular cloud data warehouses like Snowflake can provide the scalability needed as your business grows.

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IBM Journey to AI blog

SEPTEMBER 19, 2023

By analyzing datasets, data scientists can better understand their potential use in an algorithm or machine learning model. The data science lifecycle Data science is iterative, meaning data scientists form hypotheses and experiment to see if a desired outcome can be achieved using available data.

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phData

MARCH 29, 2024

Operational Risks: Uncover operational risks such as data loss or failures in the event of an unforeseen outage or disaster. Performance Optimization: Locate and fix bottlenecks in your data pipelines so that you can get the most out of your Snowflake investment.

Data Engineering 52

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phData

FEBRUARY 5, 2024

Other features include email notifications (to let you know if a job failed or is running long), job scheduling, orchestration to ensure your data gets to Snowflake when you want it, and of course, full automation of your complete data ingestion process.

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phData

OCTOBER 20, 2023

The most common example of such databases is where events are tracked. For software products or ERP backend databases, thousands of data units must be tracked and monitored. Speed: The agent on the source database will filter the data before sending it through the data pipeline.

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DagsHub

AUGUST 23, 2024

Data Quality Dimensions Data quality dimensions are the criteria that are used to evaluate and measure the quality of data. These include the following: Accuracy indicates how correctly data reflects the real-world entities or events it represents. It is SQL-based and integrates well with modern data warehouses.

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phData

JANUARY 15, 2024

This strategic replication ensures that even if an issue arises in one area, your data remains accessible from another, creating a safety net for your critical information. In the face of unexpected events or outages, Snowflake introduces failover mechanisms.

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The MLOps Blog

MARCH 15, 2023

ETL usually stands for “Extract, Transform and Load,” and it refers to a process in data warehousing. Sourcing the data In our case, the data was provided by our client, which was a product-based organization. The data pipelines can be scheduled as event-driven or be run at specific intervals the users choose.

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Pickl AI

SEPTEMBER 5, 2024

The platform’s integration with Azure services ensures a scalable and secure environment for Data Science projects. 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.

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Alation

APRIL 14, 2022

Data pipeline orchestration. Moving/integrating data in the cloud/data exploration and quality assessment. Supports the ability to interact with the actual data and perform analysis on it. This provides the facility a time or event for a job to run and offers useful post-run information. Scheduling.

Data Governance 59

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phData

OCTOBER 28, 2024

However, if the tool supposes an option where we can write our custom programming code to implement features that cannot be achieved using the drag-and-drop components, it broadens the horizon of what we can do with our data pipelines. The default value is 360 seconds. If not, it will retry after a certain duration (E.g., 30 minutes).

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Python ETL AWS Database 52

Alation

APRIL 19, 2022

Data modernization is the process of transferring data to modern cloud-based databases from outdated or siloed legacy databases, including structured and unstructured data. In that sense, data modernization is synonymous with cloud migration. Access the resources your data applications need — no more, no less.

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