Data Science Blog

NOVEMBER 15, 2023

In addition to Business Intelligence (BI), Process Mining is no longer a new phenomenon, but almost all larger companies are conducting this data-driven process analysis in their organization. The Event Log Data Model for Process Mining Process Mining as an analytical system can very well be imagined as an iceberg.

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Data Modeling Data Models Business Intelligence Business Intelligence 245

Dataversity

MAY 29, 2023

A unified data model allows businesses to make better-informed decisions. By providing organizations with a more comprehensive view of the data sources they’re using, which makes it easier to understand their customers’ experiences. appeared first on DATAVERSITY.

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Data Science Dojo

MAY 10, 2023

In the current landscape, data science has emerged as the lifeblood of organizations seeking to gain a competitive edge. As the volume and complexity of data continue to surge, the demand for skilled professionals who can derive meaningful insights from this wealth of information has skyrocketed.

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Data Science Dojo

MARCH 8, 2024

This blog delves into a detailed comparison between the two data management techniques. In today’s digital world, businesses must make data-driven decisions to manage huge sets of information. Hence, databases are important for strategic data handling and enhanced operational efficiency.

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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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Towards AI

NOVEMBER 12, 2024

But with this rapid growth comes a key challenge: ensuring that AI-generated information is precise, trustworthy, and free from “hallucinations”. In AI, hallucinations refer to errors where the model generates incorrect or invented information.

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AI AI Data Modeling Data Models 111

Data Science Dojo

APRIL 7, 2025

In the digital age, data is powe r. But with great power comes great responsibility, especially when it comes to protecting peoples personal information. One of the ways to make sure that data is used responsibly is through data anonymization. These concerns arent just hypothetical.

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Flipboard

FEBRUARY 14, 2023

Time-varying entities may contain multiple time-varying and static attributes, making mapping them a particular challenge.

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Data Modeling Data Models Database Big Data 123

Dataconomy

JUNE 10, 2022

The vast majority of data created today is unstructured – that is, it’s information in many different forms that don’t follow conventional data models. According to IDC, 80% of all data by 2025. That makes it difficult to store and manage in a standard relational database.

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Database Data Modeling Data Models 170

Flipboard

NOVEMBER 20, 2024

By narrowing down the search space to the most relevant documents or chunks, metadata filtering reduces noise and irrelevant information, enabling the LLM to focus on the most relevant content. By combining the capabilities of LLM function calling and Pydantic data models, you can dynamically extract metadata from user queries.

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Data Science Dojo

FEBRUARY 6, 2025

It is a fundamental step in AI training as it provides the necessary context and structure that models need to learn from raw data. It enables AI systems to recognize patterns, understand them, and make informed predictions. Video Annotation It is similar to image annotation but is applied to video data.

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Flipboard

JULY 24, 2023

Researchers from many universities build open-source projects which contribute to the development of the Data Science domain. It is also called the second brain as it can store data that is not arranged according to a present data model or schema and, therefore, cannot be stored in a traditional relational database or RDBMS.

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Natural Language Processing Artificial Intelligence Artificial Intelligence Data Science 122

Flipboard

DECEMBER 22, 2024

Nature Biomedical Engineering - Foundation models can be advantageously harnessed to estimate missing data in multimodal biomedical datasets and to generate realistic synthetic samples.

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Data Modeling Data Models Machine Learning Machine Learning 81

Data Science Dojo

APRIL 18, 2023

Whether you’re located anywhere in the world or belong to any profession, you can still develop the expertise needed to be a skilled data analyst. Who are data analysts? Data analysts are professionals who use data to identify patterns, trends, and insights that help organizations make informed decisions.

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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.

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Dataconomy

MARCH 6, 2025

Data vault is not just a method; its an innovative approach to data modeling and integration tailored for modern data warehouses. As businesses continue to evolve, the complexity of managing data efficiently has grown. As businesses continue to evolve, the complexity of managing data efficiently has grown.

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Data Science Dojo

OCTOBER 31, 2024

Specialized Industry Knowledge The University of California, Berkeley notes that remote data scientists often work with clients across diverse industries. Whether it’s finance, healthcare, or tech, each sector has unique data requirements.

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Data Science Dojo

FEBRUARY 23, 2024

You can upload your data files to this GPT that it can then analyze. Once you provide relevant prompts of focus to the GPT, it can generate appropriate data visuals based on the information from the uploaded files. Other than the advanced data analysis, it can also deal with image conversions.

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Data Science Dojo

JULY 21, 2023

DAX formulas include functions, operators, and values to perform advanced calculations and queries on data in related tables and columns in tabular data models. The Basics of DAX for Data Analysis DAX is a powerful language that can be used to create dynamic and informative reports that can help you make better decisions.

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Data Science Dojo

JULY 21, 2023

DAX formulas include functions, operators, and values to perform advanced calculations and queries on data in related tables and columns in tabular data models. The Basics of DAX for Data Analysis DAX is a powerful language that can be used to create dynamic and informative reports that can help you make better decisions.

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Data Analysis Data Analysis Power BI Data Modeling 195

Hacker News

NOVEMBER 19, 2024

Here are a few of the things that you might do as an AI Engineer at TigerEye: - Design, develop, and validate statistical models to explain past behavior and to predict future behavior of our customers’ sales teams - Own training, integration, deployment, versioning, and monitoring of ML components - Improve TigerEye’s existing metrics collection and (..)

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Dataversity

FEBRUARY 14, 2024

This requires a strategic approach, in which CxOs should define business objectives, prioritize data quality, leverage technology, build a data-driven culture, collaborate with […] The post Facing a Big Data Blank Canvas: How CxOs Can Avoid Getting Lost in Data Modeling Concepts appeared first on DATAVERSITY.

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Dataconomy

MARCH 17, 2025

The purpose of NLQ The main goal of NLQ is to democratize access to analytical tools, making it easier for users without a deep understanding of data management to derive insights. By simplifying the querying process, NLQ allows for quicker and more efficient information retrieval.

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Natural Language Processing Power BI Analytics Analytics 91

Dataconomy

OCTOBER 15, 2024

Forbes reports that global data production increased from 2 zettabytes in 2010 to 44 ZB in 2020, with projections exceeding 180 ZB by 2025 – a staggering 9,000% growth in just 15 years, partly driven by artificial intelligence. However, raw data alone doesn’t equate to actionable insights.

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Data Modeling Data Models Analytics Analytics 113

Data Science Dojo

AUGUST 19, 2024

To address the bias-variance trade-off: Regularization: Techniques like L1 and L2 regularization can help prevent overfitting by penalizing complex models. Ensemble methods: Combining multiple models can reduce variance and improve generalization. Model selection: Carefully selecting the appropriate model complexity for the given task.

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Flipboard

JULY 26, 2023

Fact and dimension tables are crucial components of Power BI data models. Enhance your data analysis by learning their differences. In Power BI, fact …

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Data Science Dojo

FEBRUARY 9, 2023

From data discovery and cleaning to report creation and sharing, we will delve into the key steps that can be taken to turn data into decisions. A data analyst is a professional who uses data to inform business decisions. Check out this course and learn Power BI today!

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AWS Machine Learning Blog

NOVEMBER 18, 2024

This complexity hinders customers from making informed decisions. As a result, customers face challenges in selecting the right insurance coverage, while insurance aggregators and agents struggle to provide clear and accurate information.

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Smart Data Collective

MAY 16, 2022

Data management software helps in reducing the cost of maintaining the data by helping in the management and maintenance of the data stored in the database. It also helps in providing visibility to data and thus enables the users to make informed decisions. They are a part of the data management system.

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Data Science Dojo

MARCH 7, 2023

As data science evolves and grows, the demand for skilled data scientists is also rising. A data scientist’s role is to extract insights and knowledge from data and to use this information to inform decisions and drive business growth.

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Data Scientist Exploratory Data Analysis Data Science Data Visualization 221

Dataversity

AUGUST 12, 2024

One of the most important questions about using AI responsibly has very little to do with data, models, or anything technical. How can […] The post Ask a Data Ethicist: How Can We Set Realistic Expectations About AI? It has to do with the power of a captivating story about magical thinking.

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AI AI Data Modeling Data Models 105

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.

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Data Science Dojo

SEPTEMBER 9, 2024

Fairness aims to prevent discrimination and bias in AI models, addressing risks where AI might reinforce harmful stereotypes or create unequal opportunities in areas like hiring, lending, or law enforcement. Security is about safeguarding AI systems from threats like adversarial attacks, model theft, and data tampering.

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Tableau

JULY 25, 2024

Spencer Czapiewski July 25, 2024 - 5:54pm Thomas Nhan Director, Product Management, Tableau Lari McEdward Technical Writer, Tableau Expand your data modeling and analysis with Multi-fact Relationships, available with Tableau 2024.2. You may have heard of Multi-fact Relationships informally referred to as “shared dimensions.”

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Tableau Data Modeling Data Models Data Silos 76

phData

SEPTEMBER 11, 2023

Location Based RLS An organization wants specific subsets of users only to see information about locations that are specific to them (City/State/Region/Country, etc.) Ex: We are the VP of Finance for the Western region and should only see data for that specific area. a regional sales team needs to view data for their region).

Power BI 101

Power BI Data Modeling Data Models Data Governance 101

AWS Machine Learning Blog

DECEMBER 9, 2024

SageMaker with MLflow now supports AWS PrivateLink , which enables you to transfer critical data from your VPC to MLflow Tracking Servers through a VPC endpoint. We specify the security group and subnets information in VpcConfig. We specify the security group and subnets information in VpcConfig.

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Smart Data Collective

AUGUST 9, 2022

NoSQL databases became possible fairly recently, in the late 2000s, all thanks to the decrease in the price of data storage. Just like that, the need for complex and difficult-to-manage data models has dissipated to give way to better developer productivity. Databases of this type store data in edges and nodes.

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