Cambridge Intelligence

NOVEMBER 20, 2023

This Azure Cosmos DB tutorial shows you how to integrate Microsoft’s multi-model database service with our graph and timeline visualization SDKs to build an interactive graph application. There’s support for MongoDB, PostgreSQL, Apache Cassandra, Apache Gremlin, and Tables, and our data visualization toolkits work with all of them.

Azure 64

Azure Database Data Modeling Data Models 64

ODSC - Open Data Science

MARCH 30, 2023

Using Azure ML to Train a Serengeti Data Model, Fast Option Pricing with DL, and How To Connect a GPU to a Container Using Azure ML to Train a Serengeti Data Model for Animal Identification In this article, we will cover how you can train a model using Notebooks in Azure Machine Learning Studio.

Azure 52

Azure ML ML Data Modeling 52

Data Science Connect

JANUARY 27, 2023

Understanding how data warehousing works and how to design and implement a data warehouse is an important skill for a data engineer. Learn about data modeling: Data modeling is the process of creating a conceptual representation of data.

Data Engineering 130

Data Engineering Data Engineering Data Engineering Data Engineer 130

Mlearning.ai

DECEMBER 21, 2023

Explore ML architectural patterns in Azure for classic and evolving needs – streaming data, model monitoring, and multiple models pipeline Continue reading on MLearning.ai »

Azure 52

Azure ML ML Data Modeling 52

Data Science Dojo

FEBRUARY 9, 2023

It allows users to connect to a variety of data sources, perform data preparation and transformations, create interactive visualizations, and share insights with others. The platform includes features such as data modeling, data discovery, data analysis, and interactive dashboards.

Power BI 221

Power BI Data Analyst Data Visualization Data Analysis 221

Revolutions

JANUARY 21, 2021

by Hong Ooi Last week , I announced AzureCosmosR, an R interface to Azure Cosmos DB , a fully-managed NoSQL database service in Azure. Explaining what Azure Cosmos DB is can be tricky, so here’s an excerpt from the official description : Azure Cosmos DB is a fully managed NoSQL database for modern app development.

Azure 40

Azure SQL Database Administration Database 40

phData

MAY 25, 2023

One big issue that contributes to this resistance is that although Snowflake is a great cloud data warehousing platform, Microsoft has a data warehousing tool of its own called Synapse. In a perfect world, Microsoft would have clients push even more storage and compute to its Azure Synapse platform.

Power BI 84

Power BI Analytics Analytics Azure 84

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 Modeling Data Models Data Warehouse 52

ODSC - Open Data Science

JANUARY 25, 2023

The Azure ML team has long focused on bringing you a resilient product, and its latest features take one giant leap in that direction, as illustrated in the graph below (Figure 1). Continue reading to learn more about Azure ML’s latest announcements. This is the motivation behind several of Azure ML’s latest features.

Machine Learning 59

Machine Learning Machine Learning Azure ML 59

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 Modeling 52

Data Modeling Data Models Apache Kafka Data Lakes 52

Smart Data Collective

OCTOBER 19, 2022

MongoDB is deployable anywhere, and the MongoDB Atlas database-as-a-service can be deployed on AWS, Azure, and Google Cloud Platform (GCP). What Are Their Ranges of Data Models? MongoDB has a wider range of datatypes than DynamoDB, even though both databases can store binary data.

Big Data 132

Big Data Big Data Database AWS 132

Women in Big Data

NOVEMBER 27, 2024

By maintaining historical data from disparate locations, a data warehouse creates a foundation for trend analysis and strategic decision-making. Snowflake Snowflake is a cloud-based data warehousing platform that offers a highly scalable and efficient architecture designed for performance and ease of use.

Data Warehouse 59

Data Warehouse Big Data Big Data Azure 59

Hacker News

JULY 18, 2023

What if you could automatically shard your PostgreSQL database across any number of servers and get industry-leading performance at scale without any special data modelling steps? Schema-based sharding has almost no data modelling restrictions or special steps compared to unsharded PostgreSQL.

Database 123

Database SQL Data Models Data Modeling 123

Dataconomy

SEPTEMBER 4, 2023

Key features of cloud analytics solutions include: Data models , Processing applications, and Analytics models. Data models help visualize and organize data, processing applications handle large datasets efficiently, and analytics models aid in understanding complex data sets, laying the foundation for business intelligence.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

ODSC - Open Data Science

JUNE 12, 2023

This article is an excerpt from the book Expert Data Modeling with Power BI, Third Edition by Soheil Bakhshi, a completely updated and revised edition of the bestselling guide to Power BI and data modeling. No-code/low-code experience using a diagram view in the data preparation layer similar to Dataflows.

Power BI 52

Power BI Data Warehouse ETL Data Preparation 52

Pickl AI

FEBRUARY 18, 2025

Summary: Power BI is a business analytics tool transforming data into actionable insights. Key features include AI-powered analytics, extensive data connectivity, customisation options, and robust data modelling. Key Takeaways It transforms raw data into actionable, interactive visualisations. Why Power BI?

Power BI 52

Power BI Azure SQL Business Intelligence 52

Smart Data Collective

JUNE 4, 2021

Since the field covers such a vast array of services, data scientists can find a ton of great opportunities in their field. Data scientists use algorithms for creating data models. These data models predict outcomes of new data. Data science is one of the highest-paid jobs of the 21st century.

Data Science 133

Data Science Exploratory Data Analysis Machine Learning Machine Learning 133

Pickl AI

NOVEMBER 22, 2024

Key Features Integration with Microsoft Products : Seamlessly connects with Excel, Azure, and other Microsoft services. Real-Time Data Monitoring : Allows users to track metrics in real-time. Key Features Associative Data Model : Users can explore data freely without being confined to predefined queries.

Data Visualization 52

Data Visualization Big Data Big Data Power BI 52

Smart Data Collective

NOVEMBER 24, 2020

Features: intuitive visualizations on-premise and cloud report sharing dashboard and report publishing to the web indicators of data patterns integration with third-party services (Salesforce, Google Analytics, Zendesk, Azure, Mailchimp, etc.). Unique feature: custom visualizations to fit your business needs better. SAP Lumira.

Business Intelligence 134

Business Intelligence Business Intelligence Power BI Augmented Analytics 134

Cambridge Intelligence

OCTOBER 19, 2023

That’s why our data visualization SDKs are database agnostic: so you’re free to choose the right stack for your application. Multi-model databases combine graphs with two other NoSQL data models – document and key-value stores. Transactional, analytical, or both…?

Database 59

Database Azure SQL Analytics 59

Pickl AI

MARCH 4, 2024

Loading data into Power BI is a straightforward process. Using Power Query, users can connect to various data sources such as Excel files, SQL databases, or cloud services like Azure. Once connected, data can be transformed and loaded into Power BI for analysis. How do you handle real-time data streaming in Power BI?

Power BI 52

Power BI Data Analysis Data Analysis Data Modeling 52

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 Engineering Data Engineer 52

Snorkel AI

OCTOBER 18, 2023

Claims data is often noisy, unstructured, and multi-modal. Manually aligning and labeling this data is laborious and expensive, but—without high-quality representative training data—models are likely to make errors and produce inaccurate results.

AI 64

AI AI Machine Learning Machine Learning 64

Snorkel AI

OCTOBER 18, 2023

Claims data is often noisy, unstructured, and multi-modal. Manually aligning and labeling this data is laborious and expensive, but—without high-quality representative training data—models are likely to make errors and produce inaccurate results.

AI 59

AI AI Machine Learning Machine Learning 59

Hacker News

NOVEMBER 14, 2023

The data from D10 was never actually transferred to D11, meaning the business is now using 2 systems instead of 1. D11 data model doesn’t really support the data in D10 either. Technology teams demanded that BackEnd be built in Microsoft Azure Pipelines, to comply with “Strategic Vision”.

Power BI 128

Power BI Database Algorithm Azure 128

ODSC - Open Data Science

APRIL 6, 2023

But its status as the go-between for programming and data professionals isn’t its only power. Within SQL you can also filter data, aggregate it and create valuations, manipulate data, update it, and even do data modeling. Finally, cloud services.

SQL 98

SQL Data Scientist Database Data Science 98

Snorkel AI

OCTOBER 18, 2023

Claims data is often noisy, unstructured, and multi-modal. Manually aligning and labeling this data is laborious and expensive, but—without high-quality representative training data—models are likely to make errors and produce inaccurate results.

AI 52

AI AI ML ML 52

Mlearning.ai

FEBRUARY 16, 2023

The platform enables quick, flexible, and convenient options for storing, processing, and analyzing data. The solution was built on top of Amazon Web Services and is now available on Google Cloud and Microsoft Azure. Use Multiple Data Models With on-premise data warehouses, storing multiple copies of data can be too expensive.

Data Warehouse 52

Data Warehouse Business Intelligence Business Intelligence Database 52

DagsHub

APRIL 21, 2024

Amazon SageMaker pricing is based on a pay-as-you-go model, with costs calculated based on factors such as instance type, storage usage, and training hours. Similar to SageMaker, Azure ML offers a range of tools and services for the entire machine learning lifecycle, from data preparation and model development to deployment and monitoring.

Machine Learning 59

Machine Learning Machine Learning ML ML 59

phData

JULY 11, 2023

Power BI Datamarts provides a low/no code experience directly within Power BI Service that allows developers to ingest data from disparate sources, perform ETL tasks with Power Query, and load data into a fully managed Azure SQL database. Blog: Data Modeling Fundamentals in Power BI. a.

Power BI 40

Power BI SQL Azure ETL 40

O'Reilly Media

OCTOBER 19, 2021

We need robust versioning for data, models, code, and preferably even the internal state of applications—think Git on steroids to answer inevitable questions: What changed? As a commercial product, Databricks provides a managed environment that combines data-centric notebooks with a proprietary production infrastructure.

ML 145

ML ML Data Scientist AWS 145

Pickl AI

NOVEMBER 28, 2024

Model Evaluation and Tuning After building a Machine Learning model, it is crucial to evaluate its performance to ensure it generalises well to new, unseen data. Model evaluation and tuning involve several techniques to assess and optimise model accuracy and reliability.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

DagsHub

DECEMBER 11, 2023

DagsHub DagsHub is a centralized Github-based platform that allows Machine Learning and Data Science teams to build, manage and collaborate on their projects. In addition to versioning code, teams can also version data, models, experiments and more. However, these tools have functional gaps for more advanced data workflows.

Machine Learning 98

Machine Learning Machine Learning Data Lakes Big Data 98

Precisely

MARCH 9, 2023

Processing speeds were considerably slower than they are today, so large volumes of data called for an approach in which data was staged in advance, often running ETL (extract, transform, load) processes overnight to enable next-day visibility to key performance indicators.

Data Warehouse 59

Data Warehouse Data Lakes Hadoop Big Data 59

Pickl AI

JUNE 7, 2024

Azure Data Factory Azure Data Factory is a cloud-based ETL service offered by Microsoft that facilitates the creation of data workflows for moving and transforming data at scale. Flexibility: Users can interact with Data Factory through a no-code graphical interface or a command-line interface.

ETL 40

ETL Data Pipeline Data Quality Data Warehouse 40

Pickl AI

JULY 25, 2023

Skills and Tools of Data Engineers Data Engineering requires a unique set of skills, including: Database Management: SQL, NoSQL, NewSQL, etc. Data Warehousing: Amazon Redshift, Google BigQuery, etc. Data Modeling: Entity-Relationship (ER) diagrams, data normalization, etc.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

phData

SEPTEMBER 28, 2023

Attach a Common Data Model Folder (preview) When you create a Dataflow from a CDM folder, you can establish a connection to a table authored in the Common Data Model (CDM) format by another application. With the import option, users can create a new version of the Dataflow while the original Dataflow remains unchanged.

Power BI 78

Power BI Data Preparation Machine Learning Machine Learning 78