Data Science Dojo

OCTOBER 31, 2024

Key Skills Proficiency in SQL is essential, along with experience in data visualization tools such as Tableau or Power BI. Strong analytical skills and the ability to work with large datasets are critical, as is familiarity with data modeling and ETL processes.

Data Science 195

Data Science Data Scientist Machine Learning Machine Learning 195

AWS Machine Learning Blog

FEBRUARY 7, 2024

Select options and train the model The next step towards building and training a fraud detector model is to define the business activity (event) to evaluate for the fraud. Defining an event involves setting the variables in your dataset, an entity initiating the event, and the labels that classify the event.

ML 135

ML ML AWS Data Profiling 135

Women in Big Data

APRIL 4, 2025

Women in Big Data and LinkedIn hosted an empowering event The Responsible AI at Scale in LinkedIn HQ in Sunnyvale, CA on March 13 th , 2025, for people passionate about ethics, transparency and shaping the AI technologies of the future. I cant wait for the next Women in Big Data event!

Big Data 52

Big Data Big Data AI AI 52

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

Dataconomy

OCTOBER 15, 2024

I’ve found that while calculating automation benefits like time savings is relatively straightforward, users struggle to estimate the value of insights, especially when dealing with previously unavailable data. We were developing a data model to provide deeper insights into logistics contracts.

Data Modeling 113

Data Modeling Data Models Analytics Analytics 113

AWS Machine Learning Blog

JUNE 22, 2023

Working with AWS, Light & Wonder recently developed an industry-first secure solution, Light & Wonder Connect (LnW Connect), to stream telemetry and machine health data from roughly half a million electronic gaming machines distributed across its casino customer base globally when LnW Connect reaches its full potential.

AWS 110

AWS ML ML Machine Learning 110

Dataversity

JANUARY 13, 2021

In marketing, artificial intelligence (AI) is the process of using data models, mathematics, and algorithms to generate insights that marketers can use. Marketers use insights gained from AI to guide future decisions on event spending, strategy, and content topics. What Is Artificial Intelligence Marketing? AI also […].

Artificial Intelligence 69

Artificial Intelligence Artificial Intelligence Data Modeling Data Models 69

Data Science Dojo

AUGUST 19, 2024

Interpolation: Use interpolation methods to estimate missing values in time series data. Model-based imputation: Train a model to predict missing values based on other features in the dataset. Networking Platforms: Meetup: Attend AI-related meetups and networking events to connect with professionals in the field.

AI 364

AI AI Machine Learning Machine Learning 364

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

Smart Data Collective

SEPTEMBER 16, 2020

Regardless of your industry, whether it’s an enterprise insurance company, pharmaceuticals organization, or financial services provider, it could benefit you to gather your own data to predict future events. From a predictive analytics standpoint, you can be surer of its utility. Deep Learning, Machine Learning, and Automation.

Predictive Analytics 139

Predictive Analytics Analytics Analytics Decision Trees 139

Hacker News

JULY 4, 2023

var ( // Arrow schema for the OTLP Arrow Traces record (without attributes, links, and events). An overview of the different components and events used to implement this approach is depicted in figure 1. If a field exists in the data but is not included in the schema, the encoder will trigger a missing field event.

Data Modeling 123

Data Modeling Data Models Data Observability 123

Towards AI

OCTOBER 10, 2024

Here is the prompt that we utilized for our task (incorrect markdown rendering on the Medium side): You are an intelligent assistant designed to analyze product reviews and extract specific information to populate a structured data model. Your task is to process a given product review text and extract the following fields:1.

Algorithm 119

Algorithm AI AI Data Modeling 119

AWS Machine Learning Blog

NOVEMBER 6, 2024

client( service_name='bedrock-runtime', region_name='us-east-1' ) Define the prompt as follows: prompt = "write an article about fictional planet Foobar" Edit the API request and put it in keyword argument as before: We use the API request of the claude-v2 model.

AWS 119

AWS Python Machine Learning Machine Learning 119

Towards AI

JULY 30, 2023

Over the years, our annual conference has grown from a 300-person event into a 2,500-person event, doubling growth every year. Our 2023 event is taking place at the MGM Grand in Las Vegas August 7–9. Join thousands of data leaders on the AI newsletter. You can learn more and sign up here.

AI 98

AI AI Artificial Intelligence Artificial Intelligence 98

AWS Machine Learning Blog

JANUARY 5, 2024

MLOps – The architecture implements a SageMaker model monitoring pipeline for continuous model quality governance by validating data and model drift as required by the defined schedule. Whenever drift is detected, an event is launched to notify the respective teams to take action or initiate model retraining.

AWS 134

AWS Data Science ML ML 134

Towards AI

MARCH 20, 2024

Graph databases and knowledge graphs are among the most widely adopted solutions for managing data represented as graphs, consisting of nodes (entities) and edges (relationships). Knowledge graphs extend the capabilities of graph databases by incorporating mechanisms to infer and derive new knowledge from the existing graph data.

Database 118

Database Data Analysis Data Analysis Data Modeling 118

Smart Data Collective

NOVEMBER 24, 2021

The thing is, previously data analytics was based on models that perpetually extended into the future; unfortunately, most of these models have become obsolete in today’s circumstances. Before the pandemic, enterprise managers lived in the illusion that all future events could be predicted.

Analytics 134

Analytics Analytics Business Intelligence Business Intelligence 134

Tableau

MARCH 19, 2024

“I liked working with numbers but I knew that accounting was not really for me, so I signed up for a course in data science which ultimately inspired me to get my Master’s degree in Data Modeling.” “A They create relevant posts on social media and inform their followers about upcoming events.”Asking

Tableau 131

Tableau Data Visualization Business Intelligence Business Intelligence 131

IBM Journey to AI blog

JULY 6, 2023

It is more challenging than ever for IT operations (ITOps) teams to maintain a complete view of their end-to-end IT environment and effectively manage events and incidents. Incident consolidation: By consolidating data from various sources, AIOps Insights reduces noise and provides a comprehensive view of incidents for faster resolution.

Artificial Intelligence 67

Artificial Intelligence Artificial Intelligence AI AI 67

DrivenData Labs

MARCH 26, 2024

We chose Power BI to make our final product due to its capacity for presenting robust numerical visualizations together with text fields, allowing us to tell a powerful story with the data. Within Power BI, we made a simple relational data model from the datasets by linking them together along common coordinates.

Power BI 264

Power BI Data Scientist Python Machine Learning 264

Smart Data Collective

NOVEMBER 18, 2020

Complex mathematical algorithms are used to segment data and estimate the likelihood of subsequent events. Every Data Scientist needs to know Data Mining as well, but about this moment we will talk a bit later. Where to Use Data Science? Data Mining Techniques and Data Visualization.

Data Mining 144

Data Mining Data Mining Data Mining Data Science 144

Dataconomy

MAY 2, 2023

By acquiring expertise in statistical techniques, machine learning professionals can develop more advanced and sophisticated algorithms, which can lead to better outcomes in data analysis and prediction. These techniques can be utilized to estimate the likelihood of future events and inform the decision-making process.

ML 110

ML ML Machine Learning Machine Learning 110

Dataversity

JULY 16, 2024

I was privileged to deliver a workshop at Enterprise Data World 2024. Publishing this review is a way to express my gratitude to the fantastic team at DATAVERSITY and Tony Shaw personally for organizing this prestigious live event.

Data Governance 59

Data Governance Data Modeling Data Models 59

Cambridge Intelligence

NOVEMBER 20, 2023

And the dates span from 1887 to 1985, so players who weren’t alive at the same time can be linked through older or younger intermediaries, which we’ll see by inspecting data timelines using KronoGraph. Which data elements should be nodes and what should connect them? I chose ‘event’ as my partition key. New to Azure Cosmos DB?

Azure 64

Azure Database Data Modeling Data Models 64

IBM Journey to AI blog

NOVEMBER 29, 2023

You can combine this data with real datasets to improve AI model training and predictive accuracy. Creating synthetic test data to expedite testing, optimization and validation of new applications and features. Using synthetic data to prevent the exposure of sensitive data in machine learning algorithms.

Data Scientist 100

Data Scientist Machine Learning Machine Learning AI 100

Cambridge Intelligence

NOVEMBER 8, 2023

Analysts rely on our data visualization toolkits to spot hidden patterns in their visualized data. They investigate these patterns and use them to predict – and, if possible, prevent – future events. What role can interactive data visualization play? I chose one containing significant earthquakes (5.5+

Clustering 64

Clustering Data Visualization Database Data Modeling 64

AWS Machine Learning Blog

FEBRUARY 21, 2025

Apache Hive was used to provide a tabular interface to data stored in HDFS, and to integrate with Apache Spark SQL. Apache HBase was employed to offer real-time key-based access to data. Data is stored in HDFS and is accessed via Hive, which provides a tabular interface to the data and integrates with Spark SQL.

Data Science 75

Data Science AWS Hadoop Data Scientist 75

phData

MARCH 11, 2024

Event Tracking : Capturing behavioral events such as page views, add-to-cart, signup, purchase, subscription, etc. Identity Resolution : Merging behavioral events and customer identifiers in an identity graph to create a single comprehensive customer profile. dbt has become the standard for modeling.

Data Warehouse 52

Data Warehouse Cloud Data Data Modeling Data Models 52

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. You can also get data science training on-demand wherever you are with our Ai+ Training platform.

Data Lakes 98

Data Lakes Data Warehouse Database Big Data 98

Cambridge Intelligence

DECEMBER 6, 2024

OSINT is about understanding the connections between individuals, entities, and events hidden within vast datasets. The graph data model is a natural fit, helping investigators make sense of even the most complex datasets. Thats where visual link analysis comes in.

Data Silos 40

Data Silos Data Analysis Data Analysis Data Modeling 40

Mlearning.ai

MAY 16, 2023

ETL Design Pattern The ETL (Extract, Transform, Load) design pattern is a commonly used pattern in data engineering. It is used to extract data from various sources, transform the data to fit a specific data model or schema, and then load the transformed data into a target system such as a data warehouse or a database.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

AWS Machine Learning Blog

NOVEMBER 21, 2024

append(qualityLabel)); // Add event listeners for your new fields speakerDropdown.on('change', function() { r.speaker = $(this).val(); append(qualityLabel)); // Add event listeners for your new fields speakerDropdown.on('change', function() { r.speaker = $(this).val(); val(option).text(option)); append(qualityCheck).append(qualityLabel));

AWS 99

AWS AI AI Natural Language Processing 99

AWS Machine Learning Blog

JULY 17, 2024

Ingesting data for support cases, Trusted Advisor checks, and AWS Health notifications into Amazon Q Business enables interactions through natural language conversations, sentiment analysis, and root cause analysis without needing to fully understand the underlying data models or schemas. How can I speed it up?

AWS 124

AWS AI AI Artificial Intelligence 124

Cambridge Intelligence

OCTOBER 25, 2023

When you design your data model, you’ll probably begin by sketching out your data in a graph format – representing entities as nodes and relationships as links. Working in a graph database means you can take that whiteboard model and apply it directly to your schema with relatively few adaptations.

Database 64

Database Data Modeling Data Models Algorithm 64

Heartbeat

JUNE 12, 2023

Data Quality: The accuracy and completeness of data can impact the quality of model predictions, making it crucial to ensure that the monitoring system is processing clean, accurate data. Model Complexity: As machine learning models become more complex, monitoring them in real-time becomes more challenging.

Machine Learning 98

Machine Learning Machine Learning ML ML 98

AWS Machine Learning Blog

APRIL 25, 2024

These services are designed for scalability, event-driven architectures, and efficient resource utilization. client("s3") o = urlparse(s3_file, allow_fragments=False) bucket = o.netloc key = o.path.lstrip("/") s3.download_file(bucket, and requirements.txt files and save it as model.tar.gz : !

AWS 122

AWS ML ML Python 122

ODSC - Open Data Science

OCTOBER 30, 2023

Remember: The right combination of keyboard efficiency and design aesthetics elevates the impact of your data visualization techniques. Data Modeling and Drill-Through Techniques Data modeling plays a crucial role in data visualization. One of the most powerful techniques in data modeling is drill-through.

Data Visualization 52

Data Visualization Power BI Data Modeling Data Models 52