Tableau

DECEMBER 7, 2022

Allison (Ally) Witherspoon Johnston Senior Vice President, Product Marketing, Tableau Bronwen Boyd December 7, 2022 - 11:16pm February 14, 2023 In the quest to become a customer-focused company, the ability to quickly act on insights and deliver personalized customer experiences has never been more important. Up to date. Let’s explore how.

Tableau 55

Tableau Data Warehouse Data Pipeline Data Visualization 55

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

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

phData

JANUARY 5, 2023

For example, an organization might move its BI platform from an on-premises data warehouse to a cloud-based platform like the Snowflake Data Cloud. This can provide organizations with greater scalability, flexibility, and cost-effectiveness and make it easier to access and analyze data from anywhere, anytime.

Analytics 52

Analytics Analytics Tableau Database 52

phData

SEPTEMBER 15, 2023

For businesses utilizing Salesforce as their Customer Relationship Management (CRM) platform, the Snowflake Data Cloud and Tableau offer an excellent solution for scalable and accurate analytics. In order to unlock the potential of these tools, your CRM data must remain synced between Salesforce and Snowflake.

Data Warehouse 52

Data Warehouse Tableau Data Silos Analytics 52

ODSC - Open Data Science

FEBRUARY 24, 2023

There are many well-known libraries and platforms for data analysis such as Pandas and Tableau, in addition to analytical databases like ClickHouse, MariaDB, Apache Druid, Apache Pinot, Google BigQuery, Amazon RedShift, etc. You can watch it on demand here.

Exploratory Data Analysis 126

Exploratory Data Analysis Data Visualization Data Analysis Data Analysis 126

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. Its open-source nature means it’s continually evolving, thanks to contributions from its user community.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

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.

Data Science 94

Data Science Analytics Analytics Data Scientist 94

Pickl AI

JULY 25, 2023

Data engineers are essential professionals responsible for designing, constructing, and maintaining an organization’s data infrastructure. They create data pipelines, ETL processes, and databases to facilitate smooth data flow and storage. Data Visualization: Matplotlib, Seaborn, Tableau, etc.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

phData

DECEMBER 12, 2023

Step 2: Analyze the Data Once you have centralized your data, use a business intelligence tool like Sigma Computing , Power BI , Tableau , or another to craft analytics dashboards. This way, decision-makers can ensure they always have the freshest data in dashboards without manually pulling a report.

Data Warehouse 52

Data Warehouse Machine Learning Machine Learning Tableau 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

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

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 5, 2024

There are many different third-party tools that work with Snowflake: Fivetran Fivetran is a tool dedicated to replicating applications, databases, events, and files into a high-performance data warehouse, such as Snowflake. How can organizations minimize downtime and ensure business continuity during the migration process to Snowflake?

SQL 52

SQL Database Data Quality Data Warehouse 52

Pickl AI

JULY 3, 2023

Familiarize yourself with data analysis techniques and tools. Learn BI technologies: Gain proficiency in popular BI tools and technologies such as Microsoft Power BI, Tableau, QlikView, or MicroStrategy. BI Developer Skills Required To excel in this role, BI Developers need to possess a range of technical and soft skills.

Business Intelligence 52

Business Intelligence Business Intelligence SQL Data Visualization 52

Pickl AI

MARCH 19, 2025

Summary: Data engineering tools streamline data collection, storage, and processing. Learning these tools is crucial for building scalable data pipelines. offers Data Science courses covering these tools with a job guarantee for career growth. Below are 20 essential tools every data engineer should know.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52