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.

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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.

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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?

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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

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?

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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.

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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.

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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

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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.

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Data Lakes Data Warehouse Database Big Data 98

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.

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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

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.

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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.

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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?

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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.

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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

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

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.

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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

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?

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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.

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Mlearning.ai

MAY 16, 2023

ETL Design Pattern The ETL (Extract, Transform, Load) design pattern is a commonly used pattern in data engineering. It is used to extract data from various sources, transform the data to fit a specific data model or schema, and then load the transformed data into a target system such as a data warehouse or a database.

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Data Engineering Data Engineering Data Engineering Data Engineer 52

Mlearning.ai

FEBRUARY 16, 2023

Today, companies are facing a continual need to store tremendous volumes of data. The demand for information repositories enabling business intelligence and analytics is growing exponentially, giving birth to cloud solutions. The platform enables quick, flexible, and convenient options for storing, processing, and analyzing data.

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Data Warehouse Business Intelligence Business Intelligence Database 52

phData

JUNE 6, 2024

These traditional CDPs are designed to gather and house their own data store—separate from the core data infrastructure. Because of this separation, data models are rigid, and the setup process is costly and lengthy. Data gets ingested, centralized, and deployed within your cloud data warehouse.

Data Warehouse 52

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Precisely

OCTOBER 23, 2023

As more organizations tap into the value of advanced analytics and AI, MDM has emerged as a vital element for trusted data and confident decisions. Very often, key business users conflate MDM with various tasks or components of data science and data management. Others regard it as a data modeling platform.

Data Quality 110

Data Quality Data Warehouse Analytics Analytics 110

Pickl AI

JULY 25, 2024

We aim to help you understand how these schemas impact data warehousing and guide you in selecting the most appropriate design for your organisation’s analytical requirements. What is Dimensional Modeling? Must Read Blogs: Exploring the Power of Data Warehouse Functionality.

Data Warehouse 52

Data Warehouse Business Intelligence Business Intelligence Database 52

phData

AUGUST 16, 2023

In the era of data modernization, organizations face the challenge of managing vast volumes of data while ensuring data integrity, scalability, and agility. It is agile, scalable, no pre-modeling required, and well-suited for fluid designs. Using dbt is one of the best choices. Contact phData!

Data Warehouse 52

Data Warehouse Data Governance SQL Data Modeling 52

Pickl AI

JANUARY 28, 2025

Research indicates that companies utilizing advanced analytics are 5 times more likely to make faster decisions than their competitors. Key Components of Business Intelligence Architecture Business Intelligence (BI) architecture is a structured framework that enables organizations to gather, analyze, and present data effectively.

Business Intelligence 52

Business Intelligence Business Intelligence ETL Data Lakes 52

IBM Journey to AI blog

OCTOBER 16, 2023

It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. How to scale AL and ML with built-in governance A fit-for-purpose data store built on an open lakehouse architecture allows you to scale AI and ML while providing built-in governance tools.

AI 88

AI AI Data Warehouse ML 88

Pickl AI

JULY 3, 2023

It is the process of converting raw data into relevant and practical knowledge to help evaluate the performance of businesses, discover trends, and make well-informed choices. Data gathering, data integration, data modelling, analysis of information, and data visualization are all part of intelligence for businesses.

Business Intelligence 52

Business Intelligence Business Intelligence SQL Data Visualization 52

phData

MARCH 11, 2024

For years, marketing teams across industries have turned to implementing traditional Customer Data Platforms (CDPs) as separate systems purpose-built to unlock growth with first-party data. ROI : Data is no longer just an analytics asset for strategic decision-making. dbt has become the standard for modeling.

Data Warehouse 52

Data Warehouse Cloud Data Data Modeling Data Models 52

Pickl AI

AUGUST 11, 2024

Additionally, it addresses common challenges and offers practical solutions to ensure that fact tables are structured for optimal data quality and analytical performance. Introduction In today’s data-driven landscape, organisations are increasingly reliant on Data Analytics to inform decision-making and drive business strategies.

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