Towards Data Science

FEBRUARY 18, 2024

How to Stream and Apply Real-Time Prediction Models on High-Throughput Time-Series Data Photo by JJ Ying on Unsplash Most of the stream processing libraries are not python friendly while the majority of machine learning and data mining libraries are python based. This design enables the re-reading of old messages.

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Kafka Python Process Google Cloud 76

ProjectPro

JANUARY 25, 2022

PySpark is a handy tool for data scientists since it makes the process of converting prototype models into production-ready model workflows much more effortless. Yahoo utilizes Apache Spark's Machine Learning capabilities to customize its news, web pages, and advertising. Why use PySpark?

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ThoughtSpot

OCTOBER 18, 2024

In the fast-paced world of software development, the efficiency of build processes plays a crucial role in maintaining productivity and code quality. This requirement prompted us to explore Build Analytics—harnessing data from our build processes to gain actionable insights.

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Building Process Pipeline-centric Database-centric 52

LinkedIn Engineering

OCTOBER 19, 2023

Authors: Bingfeng Xia and Xinyu Liu Background At LinkedIn, Apache Beam plays a pivotal role in stream processing infrastructures that process over 4 trillion events daily through more than 3,000 pipelines across multiple production data centers.

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Towards Data Science

APRIL 30, 2024

Balancing correctness, latency, and cost in unbounded data processing Image created by the author. Intro Google Dataflow is a fully managed data processing service that provides serverless unified stream and batch data processing. Apache Beam lets users define processing logic based on the Dataflow model.

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Google Cloud Process Cloud Lambda Architecture 60

Cloudera

MARCH 2, 2023

Iceberg is a high-performance open table format for huge analytic data sets. It allows multiple data processing engines, such as Flink, NiFi, Spark, Hive, and Impala to access and analyze data in simple, familiar SQL tables. This enables you to maximize utilization of streaming data at scale.

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Knowledge Hut

JULY 24, 2023

The future of SQL (Structured Query Language) is a scalding subject among professionals in the data-driven world. As data generation continues to skyrocket, the demand for real-time decision-making, data processing, and analysis increases. How is SQL Being Utilized? billion in 2022 to $154.6

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Data Science Blog: Data Engineering

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. This aspect can be applied well to Process Mining, hand in hand with BI and AI.

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Architecture Database-centric Process BI 52

LinkedIn Engineering

MARCH 23, 2023

Co-Authors: Yuhong Cheng , Shangjin Zhang , Xinyu Liu, and Yi Pan Efficient data processing is crucial in reducing learning curves, simplifying maintenance efforts, and decreasing operational complexity. By unifying these pipelines, we have saved 94% of processing time. Samza , Spark and Apache Flink ).

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Knowledge Hut

JANUARY 23, 2024

To stay on top of processes and synchronize all the elements involved, I turn to one of the key best practices in the rule book: Project Integration Management. Here’s what can be achieved through integration management: Processes and tasks can be organized and listed out. Get to know more about project description.

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Tweag

APRIL 19, 2023

To allow innovation in medical imaging with AI, we need efficient and affordable ways to store and process these WSIs at scale. Marini et al This results in a very large amount of data for a single slide, often a few gigabytes per slide, which is all stored in one big file. data import torch. or we can change the equation!

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Knowledge Hut

JANUARY 30, 2024

ITIL Processes ITIL comprises several processes that make it extremely adaptable, scalable, and diverse. These processes consist of activities with specified inputs, causes, and outputs. Let's look at some of the ITIL Processes and ideas that underpin them. This process is completed through five successive activities.

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Process Certification Portfolio Accessible 52

Snowflake

JUNE 5, 2024

With Snowpark’s existing DataFrame API , users have access to a robust framework for lazily evaluated, relational operations on data, closely resembling Spark’s conventions. pandas is the go-to data processing library for millions worldwide, including countless Snowflake users. Why introduce a distributed pandas API?

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Python Programming Language Government SQL 109

Precisely

FEBRUARY 27, 2023

Data is the fuel that drives business decisions in today’s world. To use it effectively, organizations must invest in the people, processes, and technology that enable users throughout the organization to make sound business decisions based on trusted data. That includes making a firm commitment to business agility.

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Process Finance Datasets Designing 52

Databand.ai

JULY 19, 2023

Complete Guide to Data Ingestion: Types, Process, and Best Practices Helen Soloveichik July 19, 2023 What Is Data Ingestion? Data Ingestion is the process of obtaining, importing, and processing data for later use or storage in a database. In this article: Why Is Data Ingestion Important?

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Ascend.io

NOVEMBER 14, 2024

Why Future-Proofing Your Data Pipelines Matters Data has become the backbone of decision-making in businesses across the globe. The ability to harness and analyze data effectively can make or break a company’s competitive edge. Set Up Auto-Scaling: Configure auto-scaling for your data processing and storage resources.

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Striim

SEPTEMBER 11, 2024

With data volumes and sources rapidly increasing, optimizing how you collect, transform, and extract data is more crucial to stay competitive. That’s where real-time data, and stream processing can help. We’ll answer the question, “What are data pipelines?” Table of Contents What are Data Pipelines?

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Knowledge Hut

FEBRUARY 1, 2024

What is Data Cleaning in Data Science? Data cleaning is the process of identifying and fixing incorrect data. Various fixes can be made to the data values representing incorrectness in the data. Some data pipeline systems also allow you to resume the pipeline from the middle, thus, saving time.

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Snowflake

JULY 10, 2023

Announced at Summit, we’ve recently added to Snowpark the ability to process files programmatically, with Python in public preview and Java generally available. Data engineers and data scientists can take advantage of Snowflake’s fast engine with secure access to open source libraries for processing images, video, audio, and more.

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Snowflake

JUNE 20, 2024

In the age of AI, enterprises are increasingly looking to extract value from their data at scale but often find it difficult to establish a scalable data engineering foundation that can process the large amounts of data required to build or improve models. Snowflake customers see an average of 4.6x

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Data Engineering Data Engineer Scala Engineering 92

Cloudyard

SEPTEMBER 2, 2024

This capability enables advanced analytics, custom data processing, and seamless integration of Python libraries. In this blog post, we’ll explore how to create and utilize a.Py One particularly powerful feature is the ability to import and use Python files (.py) file inside a Snowflake Python stored procedure.

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Pinterest Engineering

NOVEMBER 28, 2023

Pinterest’s real-time metrics asynchronous data processing pipeline, powering Pinterest’s time series database Goku, stood at the crossroads of opportunity. The mission was clear: identify bottlenecks, innovate relentlessly, and propel our real-time analytics processing capabilities into an era of unparalleled efficiency.

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Kafka Bytes Architecture Software Engineering 96

Knowledge Hut

MAY 3, 2024

A new breed of ‘Fast Data’ architectures has evolved to be stream-oriented, where data is processed as it arrives, providing businesses with a competitive advantage. Dean Wampler (Renowned author of many big data technology-related books) Dean Wampler makes an important point in one of his webinars.

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Pinterest Engineering

OCTOBER 11, 2024

Background Offline batch inference involves operating over a large dataset and passing the data in batches to a ML model which will generate a result for each batch. Offline batch inference jobs generally consist of a series of steps: dataloading, preprocessing, inference, post processing, and result writing.

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Datasets Software Engineering Software Engineer Metadata 63

Edureka

JULY 4, 2024

It is a cloud-based service by Amazon Web Services (AWS) that simplifies processing large, distributed datasets using popular open-source frameworks, including Apache Hadoop and Spark. Let’s see what is AWS EMR, its features, benefits, and especially how it helps you unlock the power of your big data. What is EMR in AWS?

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Data Science Blog: Data Engineering

AUGUST 22, 2024

Emerging tools now leverage AI to automate this process, identifying and correcting errors more efficiently. This shift not only saves time but also ensures a higher standard of data quality. Tools like BiG EVAL are leading data quality field for all technical systems in which data is transported and transformed.

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Data Preparation Transportation High Quality Data Data Science 52

Netflix Tech

DECEMBER 14, 2023

Engineers from across the company came together to share best practices on everything from Data Processing Patterns to Building Reliable Data Pipelines. The result was a series of talks which we are now sharing with the rest of the Data Engineering community! In this video, Sr.

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Data Engineering Weekly

NOVEMBER 11, 2024

Slack provides an excellent overview of this process. link] Hamel: Creating a LLM-as-a-Judge That Drives Business Results The author writes a comprehensive guide on creating an effective large language model (LLM) as a judge for evaluating AI products, focusing on the process of "Critique Shadowing."

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Data Engineering Data Engineer Engineering Datasets 57

Marc Lamberti

SEPTEMBER 22, 2023

That cake doesn’t get magicked into existence; it involves a process – a step-by-step recipe you carefully need to follow; otherwise, you will get something different. You can inject data at runtime, create data pipelines from YAML files, and generate tasks dynamically. What is an orchestrator? The analogy!

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Knowledge Hut

MAY 3, 2024

Cluster Computing: Efficient processing of data on Set of computers (Refer commodity hardware here) or distributed systems. It’s also called a Parallel Data processing Engine in a few definitions. Spark is utilized for Big data analytics and related processing. Why Apache Spark?

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Striim

JUNE 18, 2024

What is Real-Time Data Integration + Why is it Important? Real-time data integration includes continuous and instantaneous processes for collecting, transforming, and distributing data across systems and applications. Why is Real-Time Data Integration Important? Here are five key strategies.

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Lyft Engineering

JUNE 6, 2023

This article will cover the following topics: Performance improvement process Strategies to profile streaming pipelines Common performance problems General guidelines to improve performance Performance Improvement Process The performance improvement of any software system is not an independent and isolated task but an iterative process.

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Knowledge Hut

APRIL 23, 2024

Organizations are utilizing the enormous potential of big data to help them succeed, from consumer insights that enable personalized experiences to operational efficiency that simplifies procedures. Supply Chain Management: Big data supply chain big data use cases give merchants the ability to optimize their processes.

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Big Data Recruitment Retail Transportation 52

Hevo

JUNE 19, 2024

Oracle is widely used to store, manage, and perform complex operations on data, making it ideal for business-critical operations. You can efficiently scale your business data by hosting Oracle services on the Google Cloud Platform. Integrating these […]

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Google Cloud Utilities Cloud Data Process 52

Striim

JULY 31, 2024

At Striim, we’re excited to partner with GigaOm to present an exclusive webinar that promises to shed light on a game-changing topic in the world of data: “The Rise of Streaming Data Platforms: Embrace the Future Now.” Real-time data processing has evolved from a competitive advantage to a necessity.

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Big Data Machine Learning SQL Utilities 52

Pinterest Engineering

NOVEMBER 18, 2024

Liang Mou; Staff Software Engineer, Logging Platform | Elizabeth (Vi) Nguyen; Software Engineer I, Logging Platform | In today’s data-driven world, businesses need to process and analyze data in real-time to make informed decisions. Why is CDC Important? Support highly distributed database setup.

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Striim

JUNE 11, 2024

Better yet, AI-powered systems utilize neural networks for continuous learning and adaptation to emerging fraud tactics, which enhances predictive accuracy over time. AI vs Fraud Detection of the Past The utilization of AI in fraud detection efforts signifies a tremendous improvement over traditional techniques.

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