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

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

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

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 Models 123

Data Models Data Modeling Data Observability 123

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

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

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 117

Database Data Analysis Data Analysis Data Modeling 117

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

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 133

AWS Data Science ML ML 133

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

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 258

AI AI Machine Learning Machine Learning 258

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

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

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 78

Data Science AWS Hadoop Data Scientist 78

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 Models Data Modeling 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 Data Quality 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 Models 64

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

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 102

AWS AI AI Natural Language Processing 102

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 Engineering Data Engineering Data Engineer 52

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 126

AWS AI AI Artificial Intelligence 126

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 121

AWS ML ML Python 121

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

IBM Journey to AI blog

MARCH 29, 2024

Resolvers also provide data format specifications and enable the system to stitch together data from various sources. The API then accesses resource properties—and follows the references between resources—to get the client all the data they need from a single query to the GraphQL server.

Data Profiling 94

Data Profiling Database Data Models Data Modeling 94

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

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

IBM Journey to AI blog

MARCH 29, 2024

Metrics vary depending on the data that a team deems important and can include network traffic, latency and CPU storage. Logs: Logs are a record of events that occur within a software or application component. Histograms: Histograms measure the duration of specified events such as request duration or response size.

Database 97

Database Python Data Models Data Modeling 97

Mlearning.ai

FEBRUARY 13, 2023

These databases are designed for fast data retrieval and are ideal for applications that require quick data access and low latency, such as caching, session management, and real-time analytics. Time-Series Databases Time-Series databases are like a chronicle of events, where each event is recorded along with a timestamp ⏲.

Database 52

Database Data Modeling Data Models Big Data 52

DataRobot Blog

JUNE 9, 2022

Snowflake Summit 2022 (June 13-16) draws ever closer, and I believe it’s going to be a great event. A couple of sessions I’m excited about include the keynote The Engine & Platform Innovations Running the Data Cloud and learning how the frostbyte team conducts Rapid Prototyping of Industry Solutions. Learn more.

Cloud Data 52

Cloud Data AI AI Database 52

IBM Journey to AI blog

SEPTEMBER 19, 2023

Diagnostic analytics: Diagnostic analytics helps pinpoint the reason an event occurred. js and Tableau Data science, data analytics and IBM Practicing data science isn’t without its challenges. There can be fragmented data, a short supply of data science skills and rigid IT standards for training and deployment.

Data Science 94

Data Science Analytics Analytics Data Scientist 94