Dataconomy

JUNE 1, 2023

Microsoft has made good on its promise to deliver a simplified and more efficient Microsoft Fabric price model for its end-to-end platform designed for analytics and data workloads. Microsoft’s unified pricing model for the Fabric suite marks a significant advancement in the analytics and data market.

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Power BI Data Lakes Azure Data Silos 194

Data Science Dojo

SEPTEMBER 11, 2024

Microsoft Fabric aims to reduce unnecessary data replication, centralize storage, and create a unified environment with its unique data fabric method. Microsoft Fabric is a cutting-edge analytics platform that helps data experts and companies work together on data projects. What is Microsoft Fabric?

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Power BI Data Pipeline Data Warehouse Data Engineering 337

IBM Journey to AI blog

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

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ODSC - Open Data Science

SEPTEMBER 29, 2023

Data management problems can also lead to data silos; disparate collections of databases that don’t communicate with each other, leading to flawed analysis based on incomplete or incorrect datasets. One way to address this is to implement a data lake: a large and complex database of diverse datasets all stored in their original format.

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Dataconomy

FEBRUARY 26, 2025

Through various techniques, it allows companies to extract meaningful insights from data, leading to improved strategies and outcomes across different sectors. The importance of data mining Data mining plays a critical role in organizations by enhancing analytics initiatives and supporting various business functions across different sectors.

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Data Mining Data Mining Data Mining Data Preparation 91

Alation

FEBRUARY 20, 2020

For many enterprises, a hybrid cloud data lake is no longer a trend, but becoming reality. Due to these needs, hybrid cloud data lakes emerged as a logical middle ground between the two consumption models. earthquake, flood, or fire), where the data collected does not need to be as tightly controlled.

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Data Lakes Cloud Data AWS Tableau 52

Precisely

JUNE 24, 2024

The Precisely team recently had the privilege of hosting a luncheon at the Gartner Data & Analytics Summit in London. It was an engaging gathering of industry leaders from various sectors, who exchanged valuable insights into crucial aspects of data governance, strategy, and innovation.

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Analytics Analytics Data Governance Data Lakes 94

AWS Machine Learning Blog

APRIL 3, 2025

At the heart of this transformation is the OMRON Data & Analytics Platform (ODAP), an innovative initiative designed to revolutionize how the company harnesses its data assets. The robust security features provided by Amazon S3, including encryption and durability, were used to provide data protection.

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ODSC - Open Data Science

JUNE 1, 2023

Real-Time ML with Spark and SBERT, AI Coding Assistants, Data Lake Vendors, and ODSC East Highlights Getting Up to Speed on Real-Time Machine Learning with Spark and SBERT Learn more about real-time machine learning by using this approach that uses Apache Spark and SBERT. Well, these libraries will give you a solid start.

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AWS Machine Learning Blog

OCTOBER 20, 2023

Data and governance foundations – This function uses a data mesh architecture for setting up and operating the data lake, central feature store, and data governance foundations to enable fine-grained data access. This framework considers multiple personas and services to govern the ML lifecycle at scale.

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Smart Data Collective

AUGUST 17, 2022

You can safely use an Apache Kafka cluster for seamless data movement from the on-premise hardware solution to the data lake using various cloud services like Amazon’s S3 and others. It is because you usually see Kafka producers publish data or push it towards a Kafka topic so that the application can consume the data.

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Apache Kafka ETL Data Lakes AWS 130

Alation

FEBRUARY 13, 2020

It is about hurricanes and big events like the California wildfires, but it is also about complex things like satellite launches, for example, or big building projects. A lot of people in our audience are looking at implementing data lakes or are in the middle of big data lake initiatives.

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Data Lakes Analytics Analytics Data Engineering 52

AWS Machine Learning Blog

SEPTEMBER 27, 2024

Recent events including Tropical Cyclone Gabrielle have highlighted the susceptibility of the grid to extreme weather and emphasized the need for climate adaptation with resilient infrastructure. The model is then trained using a fully managed infrastructure, validated, and published to the Amazon SageMaker Model Registry.

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AWS Machine Learning Blog

FEBRUARY 21, 2025

If the question was Whats the schedule for AWS events in December?, AWS usually announces the dates for their upcoming # re:Invent event around 6-9 months in advance. Previously, Karam developed big-data analytics applications and SOX compliance solutions for Amazons Fintech and Merchant Technologies divisions.

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AWS Machine Learning Blog

MARCH 8, 2023

This solution helps market analysts design and perform data-driven bidding strategies optimized for power asset profitability. In this post, you will learn how Marubeni is optimizing market decisions by using the broad set of AWS analytics and ML services, to build a robust and cost-effective Power Bid Optimization solution.

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AWS Machine Learning Machine Learning Analytics 101

Smart Data Collective

AUGUST 9, 2019

Even Forbes Tech Council has written about the benefits of data lakes in Fortnite. The game’s parent company, Epic Games, processes millions of events each minute, and its mountain of data grows steadily. Processing and analyzing this data — petabytes worth — must happen somewhere.

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Big Data Big Data Data Lakes Machine Learning 97

Flipboard

NOVEMBER 27, 2024

He helps architect solutions across AI/ML applications, enterprise data platforms, data governance, and unified search in enterprises. Gi Kim is a Data & ML Engineer with the AWS Professional Services team, helping customers build data analytics solutions and AI/ML applications.

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ODSC - Open Data Science

APRIL 25, 2025

EvolvabilityIts Mostly About Data Contracts Editors note: Elliott Cordo is a speaker for ODSC East this May 1315! Be sure to check out his talk, Enabling Evolutionary Architecture in Data Engineering , there to learn about data contracts and plentymore.

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Data Engineering Data Engineering Data Engineering Data Engineer 52

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.

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ODSC - Open Data Science

MAY 7, 2024

James has been at the forefront of data architecture at Microsoft for the better part of the last nine years. Known for his thought leadership in the realm of Big Data and advanced analytics, James specializes in contemporary data architectures including the modern data warehouse, data lakehouse, data fabric, and data mesh.

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AWS Machine Learning Blog

DECEMBER 20, 2023

Whether logs are coming from Amazon Web Services (AWS), other cloud providers, on-premises, or edge devices, customers need to centralize and standardize security data. After the security log data is stored in Amazon Security Lake, the question becomes how to analyze it. Subscribe an AWS Lambda function to the SQS queue.

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AWS Machine Learning Blog

FEBRUARY 21, 2025

Thats why we use advanced technology and data analytics to streamline every step of the homeownership experience, from application to closing. This also led to a backlog of data that needed to be ingested. Analytic data is stored in Amazon Redshift. Applying for a mortgage can be complex and time-consuming.

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Data Science AWS Hadoop Data Scientist 82

Pickl AI

FEBRUARY 23, 2025

Summary: Big Data tools empower organizations to analyze vast datasets, leading to improved decision-making and operational efficiency. Ultimately, leveraging Big Data analytics provides a competitive advantage and drives innovation across various industries.

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Big Data Big Data Apache Hadoop Apache Kafka 52

AWS Machine Learning Blog

APRIL 18, 2023

Indeed, this approach combines continuous monitoring, predictive analytics, and just-in-time action. By leveraging the latest data export schema , you can obtain sensors connectivity status, gateways connectivity status, measurement classification results, closure reason code and details of asset state transition events.

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AWS Machine Learning Blog

DECEMBER 18, 2023

Among all, the native time series capabilities is a standout feature, making it ideal for a managing high volume of time-series data, such as business critical application data, telemetry, server logs and more. With efficient querying, aggregation, and analytics, businesses can extract valuable insights from time-stamped data.

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Clustering AWS Database ML 126

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.

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AWS Machine Learning Blog

APRIL 12, 2023

Traditional maintenance activities rely on a sizable workforce distributed across key locations along the BHS dispatched by operators in the event of an operational fault. With this service, industrial sensors, smart meters, and OPC UA servers can be connected to an AWS data lake with just a few clicks.

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AWS ML ML Machine Learning 114

Alation

DECEMBER 14, 2021

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. What about other data sources? To that end, AWS is making inroads into the analytics and machine learning space. Other Keynote Highlights.

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AWS Data Lakes Data Warehouse Machine Learning 52

ODSC - Open Data Science

FEBRUARY 15, 2024

You’ll learn how to load data to/from pyarrow arrays, csv and parquet files, and how to use pyarrow to quickly perform analytic operations such as filtering, aggregation, joining, and sorting. Join this session with Barr Moses to get his take on the question of whether Gen AI is a data engineering or software engineering problem.

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Data Engineering Data Engineering Data Engineering Data Engineer 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.

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Data Engineering Data Engineering Data Engineering Data Engineer 52

phData

APRIL 29, 2024

In our previous blog, Top 5 Fivetran Connectors for Financial Services , we explored Fivetran’s capabilities that address the data integration needs of the finance industry. Now, let’s cover the healthcare industry, which also has a surging demand for data and analytics, along with the underlying processes to make it happen.

SQL 52

SQL Data Warehouse Azure Cloud Data 52

Pickl AI

FEBRUARY 21, 2023

It involves using statistical and computational techniques to identify patterns and trends in the data that are not readily apparent. Data mining is often used in conjunction with other data analytics techniques, such as machine learning and predictive analytics, to build models that can be used to make predictions and inform decision-making.

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Data Mining Data Mining Data Mining Data Scientist 52

phData

JUNE 11, 2025

Between faster queries, better cost efficiency, and streamlined data management, there’s a lot to gain from a cost and performance perspective by optimizing your Snowflake account. Storage Costs Our first tip involves taking a closer look at managing how your data is stored, organized, and accessed.

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Clustering SQL Database Data Lakes 52

AWS Machine Learning Blog

SEPTEMBER 11, 2024

Common examples of time series data include sales revenue, system performance data (such as CPU utilization and memory usage), credit card transactions, sensor readings, and user activity analytics. Time series anomaly detection is the process of identifying unexpected or unusual patterns in data that unfold over time.

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DataRobot Blog

OCTOBER 3, 2017

Enterprise data architects, data engineers, and business leaders from around the globe gathered in New York last week for the 3-day Strata Data Conference , which featured new technologies, innovations, and many collaborative ideas. 2) When data becomes information, many (incremental) use cases surface.

Data Lakes 52

Data Lakes Azure Data Pipeline Hadoop 52

Precisely

JANUARY 25, 2024

Today’s cloud systems excel at high-volume data storage, powerful analytics, AI, and software & systems development. Cloud-based DevOps provides a modern, agile environment for developing and maintaining applications and services that interact with the organization’s mainframe data. Best Practice 2. Best Practice 5.

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AWS Machine Learning Blog

FEBRUARY 13, 2024

For example, the analytics team may curate features like customer profile, transaction history, and product catalogs in a central management account. Audit trail for compliance – Administrators can monitor feature usage by all accounts centrally using CloudTrail event logs. Audit logs provide centralized visibility into feature usage.

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