Dataconomy

SEPTEMBER 4, 2023

Diagnostic analytics: Diagnostic analytics goes a step further by analyzing historical data to determine why certain events occurred. By understanding the “why” behind past events, organizations can make informed decisions to prevent or replicate them. Ensure that data is clean, consistent, and up-to-date.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

Flipboard

DECEMBER 6, 2023

The Q4 Platform facilitates interactions across the capital markets through IR website products, virtual events solutions, engagement analytics, investor relations Customer Relationship Management (CRM), shareholder and market analysis, surveillance, and ESG tools. Use case overview Q4 Inc.,

SQL 167

SQL Database AWS Machine Learning 167

AWS Machine Learning Blog

APRIL 18, 2023

With the recently launched Amazon Monitron Kinesis data export v2 feature , your OT team can stream incoming measurement data and inference results from Amazon Monitron via Amazon Kinesis to AWS Simple Storage Service (Amazon S3) to build an Internet of Things (IoT) data lake. Choose Create delivery stream.

AWS 94

AWS ML ML Database 94

AWS Machine Learning Blog

DECEMBER 18, 2023

In this post, we will explore the potential of using MongoDB’s time series data and SageMaker Canvas as a comprehensive solution. MongoDB Atlas MongoDB Atlas is a fully managed developer data platform that simplifies the deployment and scaling of MongoDB databases in the cloud. Setup the Database access and Network access.

Clustering 121

Clustering AWS Database ML 121

AWS Machine Learning Blog

DECEMBER 20, 2023

A novel approach to solve this complex security analytics scenario combines the ingestion and storage of security data using Amazon Security Lake and analyzing the security data with machine learning (ML) using Amazon SageMaker. Store new security logs in an S3 bucket and queue events in Amazon Simple Queue Service (Amazon SQS).

AWS 133

AWS ML ML Algorithm 133

phData

APRIL 29, 2024

Recognizing these specific needs, Fivetran has developed a range of connectors, including dedicated applications, databases, files, and events, which can accommodate the diverse formats used by healthcare systems. Some even provide a relational layer specifically designed for analytics, while others expose APIs.

SQL 52

SQL Data Warehouse Azure Cloud Data 52

AWS Machine Learning Blog

SEPTEMBER 11, 2024

Ingestion In the ingestion layer, an AWS Lambda function retrieves sales transactions for the current minute from a PostgreSQL transactional database, transforms each record into a JSON message, and publishes it to an input Kafka topic. He is a clean code advocate and a subject-matter expert on server-less and event-driven architecture.

AWS 115

AWS ML ML Apache Kafka 115

IBM Journey to AI blog

SEPTEMBER 19, 2023

And you should have experience working with big data platforms such as Hadoop or Apache Spark. Additionally, data science requires experience in SQL database coding and an ability to work with unstructured data of various types, such as video, audio, pictures and text.

Data Science 94

Data Science Analytics Analytics Data Scientist 94

Pickl AI

JULY 30, 2024

Flow-Based Programming : NiFi employs a flow-based programming model, allowing users to create complex data flows using simple drag-and-drop operations. This visual representation simplifies the design and management of data pipelines. Guaranteed Delivery : NiFi ensures that data delivered reliably, even in the event of failures.

ETL 52

ETL Data Lakes Big Data Big Data 52

ODSC - Open Data Science

JANUARY 30, 2024

This is a pretty important job as once the data has been integrated, it can be used for a variety of purposes, such as: Reporting and analytics Business intelligence Machine learning Data mining All of this provides stakeholders and even their own teams with the data they need when they need it.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Precisely

JANUARY 25, 2024

There are three potential approaches to mainframe modernization: Data Replication creates a duplicate copy of mainframe data in a cloud data warehouse or data lake, enabling high-performance analytics virtually in real time, without negatively impacting mainframe performance. Best Practice 5.

Data Governance 69

Data Governance Database Cloud Data Data Lakes 69

AWS Machine Learning Blog

MARCH 30, 2023

How Keeper Efficiency is implemented This Bundesliga Match Fact consumes both event and positional data. Positional data is information gathered by cameras on the positions of the players and ball at any moment during the match (x-y coordinates), arriving at 25Hz. The following diagram illustrates this architecture.

Machine Learning 100

Machine Learning Machine Learning AWS ML 100

Alation

DECEMBER 14, 2021

With the database services launched soon after, developers had all the tools they needed to create applications without having to create the infrastructure to run them. How do you provide access and connect the right people to the right data? AWS has created a way to manage policies and access, but this is only for data lake formation.

AWS 52

AWS Data Lakes Data Warehouse Machine Learning 52

ODSC - Open Data Science

FEBRUARY 15, 2024

Data Pipeline Architecture — Stop Building Monoliths Elliott Cordo | Founder, Architect, Builder | Datafutures Although common, data monoliths present several challenges, especially for larger teams and organizations that allow for federated data product development. Interested in attending an ODSC event?

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

The MLOps Blog

JUNE 27, 2023

It integrates with Git and provides a Git-like interface for data versioning, allowing you to track changes, manage branches, and collaborate with data teams effectively. Dolt Dolt is an open-source relational database system built on Git.

Machine Learning 134

Machine Learning Machine Learning ML ML 134

AWS Machine Learning Blog

JUNE 12, 2024

Examples include seasonality, marketing promotions, pricing, and in-stock availability for retail sales, or temperature, length of daylight, or special events for utility demand. Local, regional, and world factors such as commodity prices, financial markets, and events such as COVID-19 can also change demand trajectory.

ML 125

ML ML AWS Data Lakes 125

DagsHub

OCTOBER 23, 2024

There are 5 stages in unstructured data management: Data collection Data integration Data cleaning Data annotation and labeling Data preprocessing Data Collection The first stage in the unstructured data management workflow is data collection. mp4,webm, etc.), and audio files (.wav,mp3,acc,

Machine Learning 52

Machine Learning Machine Learning Data Lakes AI 52

Pickl AI

NOVEMBER 4, 2024

Role of Data Engineers in the Data Ecosystem Data Engineers play a crucial role in the data ecosystem by bridging the gap between raw data and actionable insights. They are responsible for building and maintaining data architectures, which include databases, data warehouses, and data lakes.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

DataRobot Blog

MARCH 7, 2023

The DataRobot AI Platform seamlessly integrates with Azure cloud services, including Azure Machine Learning, Azure Data Lake Storage Gen 2 (ADLS), Azure Synapse Analytics, and Azure SQL database. DATAROBOT LAUNCH EVENT From Vision to Value. For more information, visit [link].

Azure 59

Azure Machine Learning Machine Learning AI 59

AWS Machine Learning Blog

AUGUST 26, 2024

At events, our teams now approach customer interactions armed with comprehensive, up-to-date information on demand. You can integrate existing data from AWS data lakes, Amazon Simple Storage Service (Amazon S3) buckets, or Amazon Relational Database Service (Amazon RDS) instances with services such as Amazon Bedrock and Amazon Q.

AWS 128

AWS AI AI K-nearest Neighbors 128

phData

FEBRUARY 14, 2023

Data integration is essentially the Extract and Load portion of the Extract, Load, and Transform (ELT) process. Data ingestion involves connecting your data sources, including databases, flat files, streaming data, etc, to your data warehouse. Snowflake provides native ways for data ingestion.

Data Warehouse 59

Data Warehouse Azure AWS Database 59

Alation

JUNE 14, 2021

Breaches are resumé generating events.”. Dan Kirsch, Analyst, Hurwitz Associates, agrees that CISOs must take responsibility, when he says that “data protection is absolutely part of the CISO’s job. Guided Navigation Guided navigation helps data stewards locate sensitive data. It seems that way these days.

Data Governance 97

Data Governance Data Lakes Data Classification Data Quality 97

phData

SEPTEMBER 27, 2024

Methods that allow our customer data models to be as dynamic and flexible as the customers they represent. In this guide, we will explore concepts like transitional modeling for customer profiles, the power of event logs for customer behavior, persistent staging for raw customer data, real-time customer data capture, and much more.

Data Modeling 52

Data Modeling Data Models Apache Kafka Data Lakes 52

Alation

MARCH 1, 2022

Airline Reporting Corporation (ARC) sells data products to travel agencies and airlines. Lineage helps them identify the source of bad data to fix the problem fast. Manual lineage will give ARC a fuller picture of how data was created between AWS S3 data lake, Snowflake cloud data warehouse and Tableau (and how it can be fixed).

Data Warehouse 52

Data Warehouse Data Lakes Cloud Data Database 52

IBM Journey to AI blog

OCTOBER 16, 2023

Curated foundation models, such as those created by IBM or Microsoft, help enterprises scale and accelerate the use and impact of the most advanced AI capabilities using trusted data. In addition to natural language, models are trained on various modalities, such as code, time-series, tabular, geospatial and IT events data.

AI 88

AI AI Data Warehouse ML 88

Pickl AI

AUGUST 9, 2024

Velocity It indicates the speed at which data is generated and processed, necessitating real-time analytics capabilities. Businesses need to analyse data as it streams in to make timely decisions. This diversity requires flexible data processing and storage solutions. Once data is collected, it needs to be stored efficiently.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

ODSC - Open Data Science

OCTOBER 3, 2024

Building an Effective OSS Management Layer for Your Data Lake Ahead of her ODSC West session on OSS management layers, the speaker discusses how data lakes can benefit from this system. Join us in a workshop where we will structure healthcare patient data for usage with LLM’s.

Data Science 40

Data Science Data Lakes Data Scientist AI 40

ODSC - Open Data Science

OCTOBER 20, 2023

HPCC Systems — The Kit and Kaboodle for Big Data and Data Science Bob Foreman | Software Engineering Lead | LexisNexis/HPCC Join this session to learn how ECL can help you create powerful data queries through a comprehensive and dedicated data lake platform. LLMs in Data Analytics: Can They Match Human Precision?

AI 52

AI AI Data Science Machine Learning 52

phData

FEBRUARY 5, 2024

Creating the databases, schemas, roles, and access grants that comprise a data system information architecture can be time-consuming and error-prone. Luckily phData has created a template-driven Provision Tool that automates onboarding users and projects to Snowflake, allowing your data teams to start producing real value immediately.

SQL 52

SQL Database Data Quality Data Warehouse 52

Mlearning.ai

FEBRUARY 16, 2023

Thus, the solution allows for scaling data workloads independently from one another and seamlessly handling data warehousing, data lakes , data sharing, and engineering. Snowflake Database Pros Extensive Storage Opportunities Snowflake provides affordability, scalability, and a user-friendly interface.

Data Warehouse 52

Data Warehouse Business Intelligence Business Intelligence Database 52

Pickl AI

SEPTEMBER 18, 2024

Read More: How Airbnb Uses Big Data and Machine Learning to Offer World-Class Service Netflix’s Big Data Infrastructure Netflix’s data infrastructure is one of the most sophisticated globally, built primarily on cloud technology. petabytes of data. What Technologies Does Netflix Use for Its Big Data Infrastructure?

Big Data 52

Big Data Big Data Apache Kafka Big Data Analytics 52

ODSC - Open Data Science

OCTOBER 15, 2023

Cloudera Cloudera is a cloud-based platform that provides businesses with the tools they need to manage and analyze data. They offer a variety of services, including data warehousing, data lakes, and machine learning. ArangoDB ArangoDB is a company that provides a database platform for graph and document data.

Machine Learning 52

Machine Learning Machine Learning Data Pipeline AI 52

phData

NOVEMBER 6, 2023

Example: models: my_project: events: # materialize all models in models/events as tables +materialized: table csvs: # this is redundant, and does not need to be set +materialized: view We can also configure the materialization type inside the dbt SQL file or the yaml file. So you will be able to update your existing materialized views.

Clustering 40

Clustering SQL Python Database 40

ODSC - Open Data Science

JULY 11, 2023

Uninterruptible Power Supply (UPS): Provides backup power in the event of a power outage, to keep the equipment running long enough to perform an orderly shutdown. Cooling systems: Data centers generate a lot of heat, so they need cooling systems to keep the temperature at a safe level. Not a cloud computer?

Data Lakes 40

Data Lakes AI AI Cloud Computing 40

phData

JULY 10, 2023

An external table is a Snowflake feature that lives outside of a database in a text-based, delimited file or in a fixed-length format file. It can be used to store data outside the database while retaining the ability to query its data. This file will be consumed in the Snowflake database using the COPY command.

Data Lakes 40

Data Lakes Azure Database AWS 40

ODSC - Open Data Science

JANUARY 18, 2024

They’ll also work with software engineers to ensure that the data infrastructure is scalable and reliable. These professionals will work with their colleagues to ensure that data is accessible, with proper access. The reason this is an important skill is that ETL is a critical process for data warehousing and business intelligence.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Pickl AI

JULY 25, 2024

Must Read Blogs: Exploring the Power of Data Warehouse Functionality. Data Lakes Vs. Data Warehouse: Its significance and relevance in the data world. Exploring Differences: Database vs Data Warehouse. Its clear structure and ease of use facilitate efficient data analysis and reporting.

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Data Warehouse Business Intelligence Business Intelligence Database 52