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

Dataconomy

SEPTEMBER 4, 2023

Cloud analytics is the art and science of mining insights from data stored in cloud-based platforms. By tapping into the power of cloud technology, organizations can efficiently analyze large datasets, uncover hidden patterns, predict future trends, and make informed decisions to drive their businesses forward.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

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. What is a Data Lake?

Data Lakes 52

Data Lakes Data Models Data Modeling Data Warehouse 52

Pickl AI

NOVEMBER 22, 2024

Summary: Big Data visualization involves representing large datasets graphically to reveal patterns, trends, and insights that are not easily discernible from raw data. Importance of Big Data Visualization The significance of Big Data Visualization lies in its ability to simplify complex datasets and facilitate decision-making.

Data Visualization 52

Data Visualization Big Data Big Data Power BI 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. Decide Which Database is Right for You.

Big Data 132

Big Data Big Data Database AWS 132

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 Business Intelligence Business Intelligence 52

Smart Data Collective

NOVEMBER 24, 2020

The current BI trends show that in the future, the BI software will be more accessible, so that even non-techie workers will rely on data insights in their working routine. Using the information in making business predictions is not a new trend. It will be used to simplify access to information and boost operations. SAP Lumira.

Business Intelligence 134

Business Intelligence Business Intelligence Power BI Augmented Analytics 134

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. How to Choose a Data Warehouse for Your Big Data Choosing a data warehouse for big data storage necessitates a thorough assessment of your unique requirements.

Data Warehouse 59

Data Warehouse Big Data Big Data Azure 59

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. Then we have some other ETL processes to constantly land the past 5 years of data into the Datamarts.

Power BI 52

Power BI Data Warehouse ETL Data Preparation 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. Tableau – Tableau is celebrated for its advanced data visualization and interactive dashboard features.

Big Data 52

Big Data Big Data Power BI Tableau 52

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. Graph databases are datastores optimized for connected data. They store information in a graph model, meaning data points can be queried in relation to their connections with other data points.

Database 59

Database Azure Analytics Analytics 59

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 Engineer Data Engineering Data Engineering 52

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. Data lakes are often used for situations in which an organization wishes to store information for possible future use.

Data Warehouse 59

Data Warehouse Data Lakes Hadoop Big Data 59

Pickl AI

MARCH 19, 2025

Understanding Data Engineering Data engineering is collecting, storing, and organising data so businesses can use it effectively. It involves building systems that move and transform raw data into a usable format. Without data engineering , companies would struggle to analyse information and make informed decisions.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

Snorkel AI

OCTOBER 18, 2023

Claims adjusters pour hours into reviewing claims documents, verifying information, coordinating with customers, and making decisions about payments. Claims data is often noisy, unstructured, and multi-modal. Traditional claims processing is manual, labor-intensive, and prone to human error.

AI 64

AI AI Machine Learning Machine Learning 64

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.

Data Warehouse 52

Data Warehouse Business Intelligence Business Intelligence Database 52

ODSC - Open Data Science

APRIL 6, 2023

For budding data scientists and data analysts, there are mountains of information about why you should learn R over Python and the other way around. Though both are great to learn, what gets left out of the conversation is a simple yet powerful programming language that everyone in the data science world can agree on, SQL.

SQL 98

SQL Data Scientist Database Data Science 98

Snorkel AI

OCTOBER 18, 2023

Claims adjusters pour hours into reviewing claims documents, verifying information, coordinating with customers, and making decisions about payments. Claims data is often noisy, unstructured, and multi-modal. Traditional claims processing is manual, labor-intensive, and prone to human error.

AI 59

AI AI Machine Learning Machine Learning 59

phData

FEBRUARY 13, 2024

By centralizing SAP ERP data in Snowflake, organizations can gain deeper insights into key business metrics, trends, and performance indicators, enabling more informed decision-making, strategic planning, and operational optimization. SAP is relatively easy to work with. What is SNP Glue?

Analytics 59

Analytics Analytics Data Scientist Data Models 59

DagsHub

DECEMBER 11, 2023

Data auditing and compliance Almost each company face data protection regulations such as GDPR, forcing them to store certain information in order to demonstrate compliance and history of data sources. In this scenario, data versioning can help companies in both internal and external audits process.

Machine Learning 98

Machine Learning Machine Learning Data Lakes Data Science 98

Snorkel AI

OCTOBER 18, 2023

Claims adjusters pour hours into reviewing claims documents, verifying information, coordinating with customers, and making decisions about payments. Claims data is often noisy, unstructured, and multi-modal. Traditional claims processing is manual, labor-intensive, and prone to human error.

AI 52

AI AI ML ML 52

Pickl AI

JUNE 18, 2024

Introduction to Power BI Project s The world of Data Analysis is constantly evolving, and Power BI stands at the forefront of this transformation. As a robust business intelligence (BI) platform, Power BI empowers users to unlock insights from data, create compelling visualizations , and drive informed decision-making.

Power BI 52

Power BI Data Analysis Data Analysis Data Visualization 52

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

For instance, understanding distributions helps select appropriate models and evaluate their likelihood, while hypothesis testing aids in validating assumptions about data. Recurrent Neural Networks (RNNs) RNNs are optimised for sequence-based data, such as time series or language.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Pickl AI

JULY 25, 2023

With expertise in programming languages like Python , Java , SQL, and knowledge of big data technologies like Hadoop and Spark, data engineers optimize pipelines for data scientists and analysts to access valuable insights efficiently. Role of Data Scientists Data Scientists are the architects of data analysis.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

Pickl AI

OCTOBER 16, 2024

Summary: Relational Database Management Systems (RDBMS) are the backbone of structured data management, organising information in tables and ensuring data integrity. Introduction RDBMS is the foundation for structured data management. They organise information into tables that facilitate easy access and manipulation.

Database 52

Database SQL Analytics Analytics 52

Pickl AI

JUNE 7, 2024

Top contenders like Apache Airflow and AWS Glue offer unique features, empowering businesses with efficient workflows, high data quality, and informed decision-making capabilities. Introduction In today’s business landscape, data integration is vital. It is part of IBM’s Infosphere Information Server ecosystem.

ETL 40

ETL Data Quality Data Pipeline Data Warehouse 40

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.

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Power BI SQL Azure ETL 40

DagsHub

OCTOBER 23, 2024

How to leverage Generative AI to manage unstructured data Benefits of applying proper unstructured data management processes to your AI/ML project. What is Unstructured Data? One thing is clear : unstructured data doesn’t mean it lacks information. data cleaning) since similar data will have similar annotations.

Machine Learning 52

Machine Learning Machine Learning Data Lakes AI 52

The MLOps Blog

JUNE 27, 2023

SageMaker Studio offers built-in algorithms, automated model tuning, and seamless integration with AWS services, making it a powerful platform for developing and deploying machine learning solutions at scale. Model versioning, lineage, and packaging : Can you version and reproduce models and experiments? Can you compare images?

Machine Learning 134

Machine Learning Machine Learning ML ML 134

DagsHub

NOVEMBER 11, 2024

In this article, we’ll explore how AI can transform unstructured data into actionable intelligence, empowering you to make informed decisions, enhance customer experiences, and stay ahead of the competition. What is Unstructured Data? We only have the video without any information.

AI 52

AI AI Data Lakes Database 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. This path is essential for accessing and manipulating the CDM data within your Dataflow.

Power BI 78

Power BI Data Preparation Machine Learning Machine Learning 78

DagsHub

OCTOBER 14, 2024

With these several trials, it is quite common to lose track of all the combinations that you might have tried out in pursuit of a better ML model. Experiment tracking is the technique of saving all the experiment-related information that you feel is most significant. in the name can also be informative.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

DagsHub

APRIL 21, 2024

By establishing standardized workflows, automating repetitive tasks, and implementing robust monitoring and governance mechanisms, MLOps enables organizations to accelerate model development, improve deployment reliability, and maximize the value derived from ML initiatives.

Machine Learning 59

Machine Learning Machine Learning ML ML 59

The MLOps Blog

NOVEMBER 30, 2022

Deeper networks mean increased hyperparameters, more experiments, and in turn more model information to save in a form that can be easily retrieved when needed. Different tools: Your repository consists of multiple tools, libraries, and infrastructure providers like Azure, AWS, and GCP.

ML 52

ML ML Machine Learning Machine Learning 52