ODSC - Open Data Science

SEPTEMBER 27, 2023

In contrast, data warehouses and relational databases adhere to the ‘Schema-on-Write’ model, where data must be structured and conform to predefined schemas before being loaded into the database. Storage Optimization: Data warehouses use columnar storage formats and indexing to enhance query performance and data compression.

Data Lakes 98

Data Lakes Data Warehouse Database Big Data 98

ODSC - Open Data Science

OCTOBER 30, 2023

In the digital era, data visualization stands as an indispensable tool in the realm of business intelligence. It represents the graphical display of data and information, transforming complex datasets into intuitive and understandable visuals. One of the most powerful techniques in data modeling is drill-through.

Data Visualization 52

Data Visualization Power BI Business Intelligence Data Modeling 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. Diagnostic analytics: Diagnostic analytics helps pinpoint the reason an event occurred.

Data Science 94

Data Science Analytics Analytics Data Scientist 94

Pickl AI

JUNE 29, 2023

Furthermore, The platform’s versatility extends beyond data analysis. This role involves configuring data inputs, managing users and permissions, and monitoring system performance. Explore Security and SIEM Splunk is widely used in cybersecurity for security information and event management (SIEM). Wrapping it up !!!

Big Data Analytics 52

Big Data Analytics Big Data Analytics Big Data Big Data 52

Pickl AI

MARCH 19, 2025

Apache Spark Apache Spark is a powerful data processing framework that efficiently handles Big Data. It supports batch processing and real-time streaming, making it a go-to tool for data engineers working with large datasets. Apache Kafka Apache Kafka is a distributed event streaming platform used for real-time data processing.

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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. Data warehousing is a vital constituent of any business intelligence operation.

Data Warehouse 52

Data Warehouse Business Intelligence Business Intelligence Database 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. Curated foundation models, such as those created by IBM or Microsoft, help enterprises scale and accelerate the use and impact of the most advanced AI capabilities using trusted data.

AI 88

AI AI Data Warehouse ML 88

Pickl AI

JULY 25, 2024

Data Warehouse: Its significance and relevance in the data world. Exploring Differences: Database vs Data Warehouse. Role in Data Warehousing and Business Intelligence Dimensional modelling plays a crucial role in data warehousing and business intelligence by structuring data to enhance performance and usability.

Data Warehouse 52

Data Warehouse Business Intelligence Business Intelligence Database 52

ODSC - Open Data Science

MAY 10, 2023

Unfortunately, even the data science industry — which should recognize tabular data’s true value — often underestimates its relevance in AI. Many mistakenly equate tabular data with business intelligence rather than AI, leading to a dismissive attitude toward its sophistication.

Data Scientist 87

Data Scientist Data Science Deep Learning Deep Learning 87

Pickl AI

AUGUST 11, 2024

These tables are called “factless fact tables” or “junction tables” They are used for modelling many-to-many relationships or for capturing timestamps of events. This schema serves as the foundation of dimensional modeling. A star schema forms when a fact table combines with its dimension tables.

Data Quality 52

Data Quality Data Warehouse Data Governance Analytics 52

Cambridge Intelligence

OCTOBER 19, 2023

Multi-model databases combine graphs with two other NoSQL data models – document and key-value stores. RDF vs property graphs Another way to categorize graph databases is by their data structure. RDF vs property graphs Another way to categorize graph databases is by their data structure.

Database 59

Database Azure SQL Analytics 59

The MLOps Blog

JANUARY 11, 2023

The result of this assessment process led to conceptualizing and designing a framework that offers an environment for building, managing, and automating processes or workflows with which the data, models, and code Ops based on the needs of individuals and across teams can be realized.

AWS 52

AWS Machine Learning Machine Learning ML 52

AWS Machine Learning Blog

MAY 30, 2023

Large language models (LLMs) are being used in chatbots for creative pursuits, academic and personal assistants, business intelligence tools, and productivity tools. You can use text-to-image models to generate abstract or realistic AI art and marketing assets.

Machine Learning 97

Machine Learning Machine Learning AI AI 97

DrivenData Labs

MARCH 26, 2024

Nicholas is a Cost Analyst with the Hunatek Professional Services Business Analytics Team, where he works on developing cost models and other analytical products. Rowan is a Business Intelligence Analyst at HunaTek. He holds a B.S. in Astronomy/Physics from the University of Virginia and an M.A.

Power BI 264

Power BI Data Scientist Python Machine Learning 264

Data Science Blog

JULY 23, 2023

Companies use Business Intelligence (BI), Data Science , and Process Mining to leverage data for better decision-making, improve operational efficiency, and gain a competitive edge. Data Mesh on Azure Cloud with Databricks and Delta Lake for Applications of Business Intelligence, Data Science and Process Mining.

Data Science 246

Data Science Azure Power BI Business Intelligence 246

Tableau

DECEMBER 1, 2021

Innovation is necessary to use data effectively in the pursuit of a better world, particularly because data continues to increase in size and richness. Four reference lines on the x-axis indicate key events in Tableau’s almost two-decade history: The first Tableau Conference in 2008. Release v1.0 IPO in 2013.

Tableau 145

Tableau ML ML Database 145

Tableau

DECEMBER 1, 2021

Innovation is necessary to use data effectively in the pursuit of a better world, particularly because data continues to increase in size and richness. Four reference lines on the x-axis indicate key events in Tableau’s almost two-decade history: The first Tableau Conference in 2008. Release v1.0 IPO in 2013.

Tableau 98

Tableau ML ML Database 98

phData

NOVEMBER 13, 2023

Efficient Data Retrieval: Quick access to metric datasets from your data platform is made possible by MetricFlow’s optimized processes. Seamless Integration with Downstream Tools: The setup process is tailored to enable consistent metric access across a variety of analytics and business intelligence tools.

Database 52

Database Business Intelligence Business Intelligence Data Silos 52