Pickl AI

APRIL 22, 2025

Summary: The snowflake schema in data warehouse organizes data into normalized, hierarchical dimension tables to reduce redundancy and enhance integrity. Introduction A snowflake schema is a sophisticated data modeling technique used in data warehousing to efficiently organize and store large volumes of data.

Data Warehouse 52

Data Warehouse Data Modeling Data Models Analytics 52

Dataconomy

JUNE 13, 2025

Data virtualization refers to a method that creates a virtual representation of data, enabling access to information from multiple sources as if it were one cohesive unit. This approach eliminates the challenges of data replication, simplifies data interaction, and supports real-time analytics.

Data Visualization 91

Data Visualization Cloud Data Data Lakes Data Warehouse 91

Dataconomy

SEPTEMBER 4, 2023

The modern corporate world is more data-driven, and companies are always looking for new methods to make use of the vast data at their disposal. Cloud analytics is one example of a new technology that has changed the game. What is cloud analytics? How does cloud analytics work?

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

databricks

JUNE 18, 2025

This is an important step forward because it gives LLMs the context they need to take actions in a more natural form.

AI 178

AI AI Data Science Business Intelligence 178

Data Science Dojo

JULY 6, 2023

Data engineering tools offer a range of features and functionalities, including data integration, data transformation, data quality management, workflow orchestration, and data visualization. Essential data engineering tools for 2023 Top 10 data engineering tools to watch out for in 2023 1.

Data Engineering 195

Data Engineering Data Engineering Data Engineer Data Engineering 195

Dataconomy

MARCH 20, 2025

By focusing on particular segments of data, Data marts enhance usability and foster agility in data handling, enabling businesses to respond swiftly to market changes. What is a data mart? Dependent data mart A dependent data mart is tightly integrated with a central data warehouse.

Data Warehouse 91

Data Warehouse ETL Data Quality Database 91

Smart Data Collective

JUNE 16, 2022

This tool can be great for handing SQL queries and other data queries. Every data scientist needs to understand the benefits that this technology offers. Online analytical processing is a computer method that enables users to retrieve and query data rapidly and carefully in order to study it from a variety of angles.

Analytics 139

Analytics Analytics Data Scientist Data Warehouse 139

Precisely

MARCH 9, 2023

As cloud computing platforms make it possible to perform advanced analytics on ever larger and more diverse data sets, new and innovative approaches have emerged for storing, preprocessing, and analyzing information. In this article, we’ll focus on a data lake vs. data warehouse.

Data Lakes 59

Data Lakes Data Warehouse Hadoop Big Data 59

Women in Big Data

NOVEMBER 27, 2024

A data warehouse is a centralized repository designed to store and manage vast amounts of structured and semi-structured data from multiple sources, facilitating efficient reporting and analysis. Begin by determining your data volume, variety, and the performance expectations for querying and reporting.

Data Warehouse 59

Data Warehouse Big Data Big Data Azure 59

Pickl AI

FEBRUARY 23, 2023

Organisations must store data in a safe and secure place for which Databases and Data warehouses are essential. You must be familiar with the terms, but Database and Data Warehouse have some significant differences while being equally crucial for businesses. What is Data Warehouse?

Data Warehouse 52

Data Warehouse Database Data Analysis Data Analysis 52

Pickl AI

JUNE 11, 2024

Summary: A data warehouse is a central information hub that stores and organizes vast amounts of data from different sources within an organization. Unlike operational databases focused on daily tasks, data warehouses are designed for analysis, enabling historical trend exploration and informed decision-making.

Data Warehouse 52

Data Warehouse ETL Data Mining Data Mining 52

phData

JUNE 13, 2023

While the front-end report visuals are important and the most visible to end users, a lot goes on behind the scenes that contribute heavily to the end product, including data modeling. In this blog, we’ll describe data modeling and its significance in Power BI. What is Data Modeling?

Power BI 93

Power BI Data Modeling Data Models Data Warehouse 93

Dataversity

JUNE 24, 2022

Data models play an integral role in the development of effective data architecture for modern businesses. They are key to the conceptualization, planning, and building of an integrated data repository that drives advanced analytics and BI.

Data Models 52

Data Models Data Modeling Data Warehouse Analytics 52

IBM Journey to AI blog

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

Data Science 94

Data Science Analytics Analytics Data Scientist 94

phData

SEPTEMBER 19, 2023

However, to fully harness the potential of a data lake, effective data modeling methodologies and processes are crucial. Data modeling plays a pivotal role in defining the structure, relationships, and semantics of data within a data lake. Consistency of data throughout the data lake.

Data Lakes 52

Data Lakes Data Models Data Modeling Data Warehouse 52

ODSC - Open Data Science

SEPTEMBER 27, 2023

In this article, we will delve into the concept of data lakes, explore their differences from data warehouses and relational databases, and discuss the significance of data version control in the context of large-scale data management. Schema Enforcement: Data warehouses use a “schema-on-write” approach.

Data Lakes 98

Data Lakes Data Warehouse Database Big Data 98

Precisely

OCTOBER 16, 2023

Rapid advancements in digital technologies are transforming cloud-based computing and cloud analytics. Big data analytics, IoT, AI, and machine learning are revolutionizing the way businesses create value and competitive advantage. In a connected mainframe/cloud environment, data is often diverse and fragmented.

Analytics 72

Analytics Analytics Big Data Analytics Big Data Analytics 72

Dataconomy

MAY 26, 2025

As businesses increasingly depend on big data to tailor their strategies and enhance decision-making, the role of these engineers becomes more crucial. They not only manage extensive data architectures but also pave the way for effective data analytics and innovative solutions. What is a big data engineer?

Big Data 91

Big Data Big Data Data Engineering Data Engineering 91

Smart Data Collective

JULY 9, 2023

ETL (Extract, Transform, Load) is a crucial process in the world of data analytics and business intelligence. By understanding the power of ETL, organisations can harness the potential of their data and gain valuable insights that drive informed choices. What is ETL? Let’s break down each step: 1.

ETL 105

ETL Data Quality Data Warehouse Analytics 105

phData

MAY 25, 2023

How to Optimize Power BI and Snowflake for Advanced Analytics Spencer Baucke May 25, 2023 The world of business intelligence and data modernization has never been more competitive than it is today. Much of what is discussed in this guide will assume some level of analytics strategy has been considered and/or defined. No problem!

Power BI 84

Power BI Analytics Analytics Azure 84

DataRobot

JANUARY 20, 2022

— Snowflake and DataRobot AI Cloud Platform is built around the need to enable secure and efficient data sharing, the integration of disparate data sources, and the enablement of intuitive operational and clinical predictive analytics. Building data communities. Action to take.

Data Science 145

Data Science Data Warehouse Analytics Analytics 145

phData

APRIL 10, 2023

In almost every modern organization, data and its respective analytics tools serve to be that big blue crayon. Users across the organization need that big blue crayon to make decisions every day, answer questions about the business, or drive changes based on data. What is Governed Self-Service Analytics? Let’s dive in.

Analytics 52

Analytics Analytics Data Governance Data Modeling 52

Tableau

MAY 11, 2022

At Tableau, we believe data is most valuable when everyone in an organization can use it to make better, data-driven decisions. At Tableau, we’re leading the industry with capabilities to connect to a wide variety of data, and we have made it a priority for the years to come. Here’s a look at what we provide today.

Tableau 98

Tableau Data Warehouse Database Data Analyst 98

Tableau

MAY 11, 2022

At Tableau, we believe data is most valuable when everyone in an organization can use it to make better, data-driven decisions. At Tableau, we’re leading the industry with capabilities to connect to a wide variety of data, and we have made it a priority for the years to come. Here’s a look at what we provide today.

Tableau 98

Tableau Data Warehouse Database Data Analyst 98

Smart Data Collective

NOVEMBER 18, 2020

Data Science is used in different areas of our life and can help companies to deal with the following situations: Using predictive analytics to prevent fraud Using machine learning to streamline marketing practices Using data analytics to create more effective actuarial processes. Where to Use Data Mining?

Data Mining 144

Data Mining Data Mining Data Mining Data Science 144

Pickl AI

MARCH 19, 2025

It helps data engineers collect, store, and process streams of records in a fault-tolerant way, making it crucial for building reliable data pipelines. Amazon Redshift Amazon Redshift is a cloud-based data warehouse that enables fast query execution for large datasets. billion in 2024 , is expected to reach $325.01

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

IBM Journey to AI blog

SEPTEMBER 17, 2024

At IBM, we’ve developed Planning Analytics, a revolutionary solution that transforms how organizations approach planning and analytics. With robust features and unparalleled scalability, IBM Planning Analytics is the preferred choice for businesses worldwide.

Analytics 40

Analytics Analytics Data Warehouse Database 40

Tableau

APRIL 18, 2022

Instead of centralizing data stores, data fabrics establish a federated environment and use artificial intelligence and metadata automation to intelligently secure data management. . At Tableau, we believe that the best decisions are made when everyone is empowered to put data at the center of every conversation.

Tableau 102

Tableau Data Quality Analytics Analytics 102

Tableau

APRIL 18, 2022

Instead of centralizing data stores, data fabrics establish a federated environment and use artificial intelligence and metadata automation to intelligently secure data management. . At Tableau, we believe that the best decisions are made when everyone is empowered to put data at the center of every conversation.

Tableau 98

Tableau Data Quality Analytics Analytics 98

ODSC - Open Data Science

JUNE 12, 2023

The Datamarts capability opens endless possibilities for organizations to achieve their data analytics goals on the Power BI platform. They all agree that a Datamart is a subject-oriented subset of a data warehouse focusing on a particular business unit, department, subject area, or business functionality.

Power BI 52

Power BI Data Warehouse ETL Data Preparation 52

Pickl AI

JULY 23, 2023

Summary: In the modern digital landscape, data analytics has emerged as a powerful tool for businesses and industries seeking valuable insights to drive decision-making and improve performance. Today, it is imperative for companies to adopt the data driven decision making processes.

Analytics 52

Analytics Analytics Predictive Analytics Data Analysis 52

phData

APRIL 20, 2023

In today’s world, data-driven applications demand more flexibility, scalability, and auditability, which traditional data warehouses and modeling approaches lack. This is where the Snowflake Data Cloud and data vault modeling comes in handy. What is Data Vault Modeling?

Data Warehouse 72

Data Warehouse Data Governance Clustering Database 72

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

Tableau

DECEMBER 7, 2022

Traditionally, organizations built complex data pipelines to replicate data. Those data architectures were brittle, complex, and time intensive to build and maintain, requiring data duplication and bloated data warehouse investments. Natively connect to trusted, unified customer data.

Tableau 98

Tableau Data Warehouse Data Pipeline Data Visualization 98

Tableau

DECEMBER 7, 2022

Traditionally, organizations built complex data pipelines to replicate data. Those data architectures were brittle, complex, and time intensive to build and maintain, requiring data duplication and bloated data warehouse investments. Natively connect to trusted, unified customer data.

Tableau 98

Tableau Data Warehouse Data Pipeline Data Visualization 98

Pickl AI

NOVEMBER 4, 2024

Summary: The fundamentals of Data Engineering encompass essential practices like data modelling, warehousing, pipelines, and integration. Understanding these concepts enables professionals to build robust systems that facilitate effective data management and insightful analysis. What is Data Engineering?

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

phData

OCTOBER 9, 2023

Understanding Data Vault Modeling Created in the 1990s by a team at Lockheed Martin, data vault modeling is a hybrid approach that combines traditional relational data warehouse models with newer big data architectures to build a data warehouse for enterprise-scale analytics.

ETL 69

ETL Clustering Data Warehouse SQL 69