Women in Big Data

DECEMBER 9, 2024

Lookers strength lies in its ability to connect to a wide variety of data sources. Examples include SQl, DWH, and Cloud based systems (Google Bigquery). With Looker, you can share dashboards and visualizations seamlessly across teams, providing stakeholders with access to real-time data.

Big Data 52

Big Data Big Data Power BI Tableau 52

phData

JULY 17, 2023

Over the past few decades, the corporate data landscape has changed significantly. The shift from on-premise databases and spreadsheets to the modern era of cloud data warehouses and AI/ LLMs has transformed what businesses can do with data. Data modeling, data cleanup, etc.

Data Warehouse 52

Data Warehouse Data Pipeline Cloud Data ETL 52

phData

OCTOBER 9, 2023

As organizations embrace the benefits of data vault, it becomes crucial to ensure optimal performance in the underlying data platform. One such platform that has revolutionized cloud data warehousing is the Snowflake Data Cloud. This can make it nearly impossible to “handwrite” these SQL queries.

ETL 69

ETL Clustering Data Warehouse SQL 69

Tableau

OCTOBER 8, 2021

Leveraging Looker’s semantic layer will provide Tableau customers with trusted, governed data at every stage of their analytics journey. With its LookML modeling language, Looker provides a unique, modern approach to define governed and reusable data models to build a trusted foundation for analytics.

Tableau 98

Tableau Analytics Analytics Machine Learning 98

Mlearning.ai

FEBRUARY 16, 2023

Data warehousing is a vital constituent of any business intelligence operation. Companies can build Snowflake databases expeditiously and use them for ad-hoc analysis by making SQL queries. Machine Learning Integration Opportunities Organizations harness machine learning (ML) algorithms to make forecasts on the data.

Data Warehouse 52

Data Warehouse Business Intelligence Business Intelligence Database 52

Alation

SEPTEMBER 7, 2021

Organizations need to ensure that data use adheres to policies (both organizational and regulatory). In an ideal world, you’d get compliance guidance before and as you use the data. Imagine writing a SQL query or using a BI dashboard with flags & warnings on compliance best practice within your natural workflow. In Summary.

Data Governance 59

Data Governance Data Scientist Data Quality Data Profiling 59

Alation

OCTOBER 27, 2022

Few actors in the modern data stack have inspired the enthusiasm and fervent support as dbt. This data transformation tool enables data analysts and engineers to transform, test and document data in the cloud data warehouse. Jason: How do you use these models? How does this help the end user?

Data Analyst 52

Data Analyst Data Scientist Analytics Analytics 52

phData

APRIL 20, 2023

Hashed PKs were introduced as a means of eliminating the bottleneck encountered by most database sequence generators, making this DV pattern ideal for customers prioritizing data loading performance and using data warehouse automation tools. Using variant columns in data vault satellites in Snowflake can provide several benefits.

Data Warehouse 72

Data Warehouse Data Governance Clustering Database 72

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.

Data Warehouse 52

Data Warehouse Analytics Analytics Cloud Data 52

Dataversity

SEPTEMBER 28, 2022

Data engineering is a fascinating and fulfilling career – you are at the helm of every business operation that requires data, and as long as users generate data, businesses will always need data engineers. The journey to becoming a successful data engineer […]. In other words, job security is guaranteed.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

phData

SEPTEMBER 27, 2024

Introduction: The Customer Data Modeling Dilemma You know, that thing we’ve been doing for years, trying to capture the essence of our customers in neat little profile boxes? For years, we’ve been obsessed with creating these grand, top-down customer data models. Yeah, that one.

Data Models 52

Data Models Data Modeling Apache Kafka Data Lakes 52