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

Dataconomy

MARCH 24, 2023

In today’s fast-paced business landscape, companies need to stay ahead of the curve to remain competitive. Business intelligence (BI) has emerged as a key solution to help companies gain insights into their operations and market trends. What is business intelligence? How to become a blockchain maestro?

Business Intelligence 70

Business Intelligence Business Intelligence Data Analysis Data Analysis 70

Dataconomy

MARCH 24, 2023

In today’s fast-paced business landscape, companies need to stay ahead of the curve to remain competitive. Business intelligence (BI) has emerged as a key solution to help companies gain insights into their operations and market trends. What is business intelligence? How to become a blockchain maestro?

Business Intelligence 70

Business Intelligence Business Intelligence Data Analysis Data Analysis 70

Pickl AI

FEBRUARY 3, 2025

Summary: A Data Warehouse consolidates enterprise-wide data for analytics, while a Data Mart focuses on department-specific needs. Data Warehouses offer comprehensive insights but require more resources, whereas Data Marts provide cost-effective, faster access to focused data.

Data Warehouse 52

Data Warehouse Analytics Analytics Database 52

Pickl AI

NOVEMBER 15, 2023

Discover the nuanced dissimilarities between Data Lakes and Data Warehouses. Data management in the digital age has become a crucial aspect of businesses, and two prominent concepts in this realm are Data Lakes and Data Warehouses. It acts as a repository for storing all the data.

Data Lakes 52

Data Lakes Data Warehouse Database ETL 52

phData

FEBRUARY 21, 2025

In this post, we will be particularly interested in the impact that cloud computing left on the modern data warehouse. We will explore the different options for data warehousing and how you can leverage this information to make the right decisions for your organization. Understanding the Basics What is a Data Warehouse?

Data Warehouse 52

Data Warehouse Cloud Data ETL Cloud Computing 52

Pickl AI

JANUARY 15, 2025

Summary: Business Intelligence tools are software applications that help organizations collect, process, analyse, and visualize data from various sources. Introduction Business Intelligence (BI) tools are essential for organizations looking to harness data effectively and make informed decisions.

Business Intelligence 52

Business Intelligence Business Intelligence Power BI Data Visualization 52

Pickl AI

JANUARY 28, 2025

Summary: Understanding Business Intelligence Architecture is essential for organizations seeking to harness data effectively. This framework includes components like data sources, integration, storage, analysis, visualization, and information delivery. What is Business Intelligence Architecture?

Business Intelligence 52

Business Intelligence Business Intelligence ETL Data Lakes 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. These tools will help make your initial data exploration process easy.

Exploratory Data Analysis 126

Exploratory Data Analysis Data Visualization Data Analysis Data Analysis 126

Smart Data Collective

JULY 9, 2023

ETL (Extract, Transform, Load) is a crucial process in the world of data analytics and business intelligence. In this article, we will explore the significance of ETL and how it plays a vital role in enabling effective decision making within businesses. What is ETL? Let’s break down each step: 1.

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ETL Data Quality Data Warehouse Analytics 105

AWS Machine Learning Blog

DECEMBER 29, 2022

Many of the RStudio on SageMaker users are also users of Amazon Redshift , a fully managed, petabyte-scale, massively parallel data warehouse for data storage and analytical workloads. It makes it fast, simple, and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools.

AWS 131

AWS Machine Learning Machine Learning Natural Language Processing 131

Smart Data Collective

APRIL 29, 2020

The extraction of raw data, transforming to a suitable format for business needs, and loading into a data warehouse. Data transformation. This process helps to transform raw data into clean data that can be analysed and aggregated. Data analytics and visualisation.

Data Warehouse 99

Data Warehouse SQL Azure ETL 99

Smart Data Collective

SEPTEMBER 26, 2021

There’s not much value in holding on to raw data without putting it to good use, yet as the cost of storage continues to decrease, organizations find it useful to collect raw data for additional processing. The raw data can be fed into a database or data warehouse. If it’s not done right away, then later.

Database 130

Database Data Visualization Big Data Big Data 130

IBM Journey to AI blog

DECEMBER 7, 2023

Online analytical processing (OLAP) database systems and artificial intelligence (AI) complement each other and can help enhance data analysis and decision-making when used in tandem. Today, OLAP database systems have become comprehensive and integrated data analytics platforms, addressing the diverse needs of modern businesses.

Data Preparation 72

Data Preparation Database Data Analysis Data Analysis 72

Dataconomy

APRIL 27, 2023

Conversely, OLAP systems are optimized for conducting complex data analysis and are designed for use by data scientists, business analysts, and knowledge workers. OLAP systems support business intelligence, data mining, and other decision support applications.

Database 159

Database Data Scientist Data Mining Data Mining 159

ODSC - Open Data Science

JUNE 12, 2023

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. The Datamart’s data is usually stored in databases containing a moving frame required for data analysis, not the full history of data.

Power BI 52

Power BI Data Warehouse ETL Data Preparation 52

ODSC - Open Data Science

FEBRUARY 8, 2023

Common databases appear unable to cope with the immense increase in data volumes. This is where the BigQuery data warehouse comes into play. BigQuery operation principles Business intelligence projects presume collecting information from different sources into one database.

Database 97

Database Data Science Big Data Big Data 97

Pickl AI

JULY 25, 2024

Must Read Blogs: Exploring the Power of Data Warehouse Functionality. Data Lakes Vs. Data Warehouse: Its significance and relevance in the data world. Exploring Differences: Database vs Data Warehouse. Explore: How Business Intelligence helps in Decision Making.

Data Warehouse 52

Data Warehouse Business Intelligence Business Intelligence Database 52

Pickl AI

JULY 3, 2023

What is Business Intelligence? Business Intelligence (BI) refers to the technology, techniques, and practises that are used to gather, evaluate, and present information about an organisation in order to assist decision-making and generate effective administrative action. billion in 2015 and reached around $26.50

Business Intelligence 52

Business Intelligence Business Intelligence SQL Data Visualization 52

phData

JANUARY 5, 2023

There’s a multitude of different reasons why an organization may consider a business intelligence (BI) platform migration. On-Premises to The Cloud This type of migration involves moving an organization’s BI platform from an on-premises environment (such as a local server or data center) to a cloud-based environment.

Analytics 52

Analytics Analytics Tableau Database 52

Pickl AI

AUGUST 1, 2023

The primary goal of Data Engineering is to transform raw data into a structured and usable format that can be easily accessed, analyzed, and interpreted by Data Scientists, analysts, and other stakeholders. Future of Data Engineering The Data Engineering market will expand from $18.2

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

IBM Journey to AI blog

SEPTEMBER 19, 2023

Data analytics is a task that resides under the data science umbrella and is done to query, interpret and visualize datasets. Data scientists will often perform data analysis tasks to understand a dataset or evaluate outcomes. Watsonx comprises of three powerful components: the watsonx.ai

Data Science 94

Data Science Analytics Analytics Data Scientist 94

phData

SEPTEMBER 19, 2023

A rigid data model such as Kimball or Data Vault would ruin this flexibility and essentially transform your data lake into a data warehouse. However, some flexible data modeling techniques can be used to allow for some organization while maintaining the ease of new data additions.

Data Lakes 52

Data Lakes Data Modeling Data Models Data Warehouse 52

Pickl AI

APRIL 26, 2024

Top 50+ Interview Questions for Data Analysts Technical Questions SQL Queries What is SQL, and why is it necessary for data analysis? SQL stands for Structured Query Language, essential for querying and manipulating data stored in relational databases. How would you segment customers based on their purchasing behaviour?

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

Pickl AI

AUGUST 9, 2024

Real-world examples illustrate their application, while tools and technologies facilitate effective hierarchical data management in various industries. Improved Data Navigation Hierarchies provide a clear structure for users to navigate through data. What are the Benefits of Using Hierarchies?

Data Warehouse 52

Data Warehouse Data Quality ETL Business Intelligence 52

AWS Machine Learning Blog

JUNE 25, 2024

To create and share customer feedback analysis without the need to manage underlying infrastructure, Amazon QuickSight provides a straightforward way to build visualizations, perform one-time analysis, and quickly gain business insights from customer feedback, anytime and on any device.

AWS 124

AWS Natural Language Processing Machine Learning Machine Learning 124

phData

JULY 10, 2024

Sigma Computing is a cloud-based business intelligence and analytics tool for collaborative data exploration, analysis, and visualization. Unlike traditional BI tools, its user-friendly interface ensures that users of all technical levels can seamlessly interact with data. Choose your desired data source type (e.g.,

SQL 52

SQL Data Warehouse Analytics Analytics 52

Pickl AI

FEBRUARY 21, 2023

Understanding the appropriate ways to use data remains critical to success in finance, education and commerce. Accordingly, data collection from numerous sources is essential before data analysis and interpretation. Furthermore, data mining can help organisations better understand their customers.

Data Mining 52

Data Mining Data Mining Data Mining Data Scientist 52

Pickl AI

DECEMBER 10, 2024

Exalytics delivers lightning-fast data analysis and visualisation capabilities. Exadata accelerates query execution and optimises storage for large-scale data management. Exalytics: The In-Memory Analytics Machine Oracle Exalytics is a pioneering solution for in-memory analytics and business intelligence.

Database 52

Database Analytics Analytics Business Intelligence 52

ODSC - Open Data Science

JANUARY 18, 2024

Like with any professional shift, it’s always good practice to take inventory of your existing data science strengths. Data scientists typically have strong skills in areas such as Python, R, statistics, machine learning, and data analysis. With that said, each skill may be used in a different manner.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

phData

JULY 14, 2023

You can store and access your structured, semi-structured, and unstructured data in one location and gain seamless access to external data with similar scale and speed. Snowflake’s cloud-based data warehouse can be used to store and query large amounts of data from multiple sources, such as ad networks, DSPs, and SSPs.

Analytics 52

Analytics Analytics Machine Learning Machine Learning 52

Pickl AI

JULY 29, 2024

Some key applications of Hadoop clusters in big data include: Data Warehousing Hadoop clusters can be used as cost-effective data warehousing solutions , storing and processing large volumes of data for business intelligence and reporting purposes.

Hadoop 52

Hadoop Clustering Big Data Big Data 52

DagsHub

NOVEMBER 11, 2024

Creating multimodal embeddings means training models on datasets with multiple data types to understand how these types of information are related. Multimodal embeddings help combine unstructured data from various sources in data warehouses and ETL pipelines.

AI 52

AI AI Data Lakes Database 52

Women in Big Data

DECEMBER 9, 2024

Introduction In the rapidly evolving landscape of data analytics, Business Intelligence (BI) tools have become indispensable for organizations seeking to leverage their big data stores for strategic decision-making. The Insight Advisor is Qliks AI-driven assistant.

Big Data 52

Big Data Big Data Power BI Tableau 52

Pickl AI

JANUARY 19, 2025

Data warehousing refers to the process of collecting, storing, and managing large volumes of structured data from various sources in a central repository known as a data warehouse. Integrated : Data from multiple sources is consolidated into a single coherent framework.

Data Mining 52

Data Mining Data Mining Data Mining Data Warehouse 52

IBM Journey to AI blog

AUGUST 4, 2023

Data fabric Data fabric architectures are designed to connect data platforms with the applications where users interact with information for simplified data access in an organization and self-service data consumption. Map a data framework –When you achieve full data democratization, what will that look like?

Data Lakes 73

Data Lakes AI AI Data Governance 73

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.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52