Pickl AI

JULY 25, 2023

Unfolding the difference between data engineer, data scientist, and data analyst. Data engineers are essential professionals responsible for designing, constructing, and maintaining an organization’s data infrastructure. Data Visualization: Matplotlib, Seaborn, Tableau, etc.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

Tableau

FEBRUARY 14, 2022

Director of Research, Tableau. I think one of the most important things I see people do right, is to make sure that you build the data foundation from the ground up correctly,” said Ali Ghodsi, CEO of Databricks. The data lakehouse is one such architecture—with “lake” from data lake and “house” from data warehouse.

AI 98

AI AI Tableau Data Scientist 98

Tableau

FEBRUARY 14, 2022

Director of Research, Tableau. I think one of the most important things I see people do right, is to make sure that you build the data foundation from the ground up correctly,” said Ali Ghodsi, CEO of Databricks. The data lakehouse is one such architecture—with “lake” from data lake and “house” from data warehouse.

AI 95

AI AI Tableau Data Scientist 95

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.

Data Warehouse 52

Data Warehouse ETL Tableau Cloud Data 52

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

Data Warehouse Business Intelligence Business Intelligence Database 52

Alation

AUGUST 30, 2022

we are introducing Alation Anywhere, extending data intelligence directly to the tools in your modern data stack, starting with Tableau. We continue to make deep investments in governance, including new capabilities in the Stewardship Workbench, a core part of the Data Governance App.

Data Governance 52

Data Governance Tableau Data Quality Data Analyst 52

Women in Big Data

OCTOBER 9, 2024

The success of any data initiative hinges on the robustness and flexibility of its big data pipeline. What is a Data Pipeline? A traditional data pipeline is a structured process that begins with gathering data from various sources and loading it into a data warehouse or data lake.

Big Data 59

Big Data Big Data Apache Kafka Data Pipeline 59

IBM Journey to AI blog

SEPTEMBER 19, 2023

Data scientists will typically perform data analytics when collecting, cleaning and evaluating data. By analyzing datasets, data scientists can better understand their potential use in an algorithm or machine learning model. Watsonx comprises of three powerful components: the watsonx.ai

Data Science 94

Data Science Analytics Analytics Data Scientist 94

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.

Data Warehouse 59

Data Warehouse Azure AWS Database 59

phData

AUGUST 9, 2024

Typically, this data is scattered across Excel files on business users’ desktops. It is extremely labor intensive, and the team wants to automate it using Snowflake and Tableau. Financial data is pulled from the ERP. Hosting the data in Snowflake’s hybrid tables may be a better choice for these applications.

ETL 52

ETL Data Warehouse Data Governance Tableau 52

Alation

MARCH 1, 2022

Through Impact Analysis, users can determine if a problem occurred with data upstream, and locate the impacted data downstream. With robust data lineage, data engineers can find and fix issues fast and prevent them from recurring. Similarly, analysts gain a clear view of how data is created.

Data Warehouse 52

Data Warehouse Data Lakes Cloud Data Database 52

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). Although a majority of use cases for tools like Tableau or Power BI rely on cached data, use cases like near real-time reporting need to utilize direct queries.

Power BI 84

Power BI Analytics Analytics Azure 84

phData

FEBRUARY 9, 2023

One popular option is the Snowflake Data Cloud , a cloud-based data warehouse that allows users to store, query, and analyze large amounts of data. Ready to take your manufacturing operations to the next level with analytics? Discover all the ways phData can help by exploring our analytics manufacturing services!

Analytics 52

Analytics Analytics Power BI Data Warehouse 52

Alation

SEPTEMBER 7, 2021

With Snowflake, data stewards have a choice to leverage Snowflake’s governance policies. First, stewards are dependent on data warehouse admins to provide information and to create and edit enforcement policies in Snowflake. Data quality details signal to users whether data can be trusted or used.

Data Governance 59

Data Governance Data Scientist Data Quality Data Profiling 59

Data Science Blog

JULY 20, 2024

Die Bedeutung effizienter und zuverlässiger Datenpipelines in den Bereichen Data Science und Data Engineering ist enorm. Es bietet vollständige Automatisierung des BI-Stacks und unterstützt ein breites Spektrum an Data Warehouses, analytischen Datenbanken und Frontends.

Azure 130

Azure SQL Power BI Data Lakes 130