LinkedIn Engineering

DECEMBER 20, 2023

In this blog post, we discuss how we are harnessing AI to help us with abuse prevention and share an overview of our infrastructure and the role it plays in identifying and mitigating abusive behavior on our platform. At the core of inference at scale lies the fusion of ML with a wealth of data.

Building 91

Building Algorithm Kafka Machine Learning 91

Knowledge Hut

OCTOBER 13, 2023

As per Microsoft, “A Power BI report is a multi-perspective view of a dataset, with visuals representing different findings and insights from that dataset. ” Reports and dashboards are the two vital components of the Power BI platform, which are used to analyze and visualize data. Read Power BI blogs and articles.

BI 52

BI Business Analyst Datasets Raw Data 52

AltexSoft

MAY 12, 2021

Particularly, we’ll present our findings on what it takes to prepare a medical image dataset, which models show best results in medical image recognition , and how to enhance the accuracy of predictions. What is to be done to acquire a sufficient dataset? labeling data by medical experts to create a ground-truth dataset.

Medical 72

Medical Healthcare Datasets Machine Learning 72

ProjectPro

JANUARY 24, 2023

One of the core features of ADF is the ability to preview your data while creating your data flows efficiently and to evaluate the outcome against a sample of data before completing and implementing your pipelines. Such features make Azure data flow a highly popular tool among data engineers.

Retail 52

Retail Big Data Data Pipeline Media 52

DareData

JULY 5, 2023

In this blog post, we aim to share practical insights and techniques based on our real-world experience in developing data lake infrastructures for our clients - let's start! The Data Lake acts as the central repository for aggregating data from diverse sources in its raw format.

Data Lake 52

Data Lake Building Raw Data ETL Tools 52

Netflix Tech

APRIL 26, 2022

The Iceberg table created by Keystone contains large blobs of unstructured data. These large unstructured blogs are not efficient for querying, so we need to transform and store this data in a different format to allow efficient queries. As our label dataset was also random, presorting facts data also did not help.

Metadata 77

Metadata Datasets Machine Learning Designing 77

ProjectPro

FEBRUARY 22, 2022

SQL Projects For Data Analysis Hoping the example above has fueled you with the zeal to enhance your programming skills in SQL , we present you with an exciting list of SQL projects for practice. You can use these SQL projects for data analysis and add them to your data analyst portfolio.

Data Analysis 52

Data Analysis SQL Project Banking 52

Rockset

NOVEMBER 1, 2022

This blog outlines best practices from customers I have helped migrate from Elasticsearch to Rockset , reducing risk and avoiding common pitfalls. In this blog, we distilled their migration journeys into 5 steps. We often see ingest queries aggregate data by time.

Database-centric 52

Database-centric SQL Pipeline-centric Aggregated Data 52

Striim

OCTOBER 11, 2024

In this architecture, compute resources are distributed across independent clusters, which can grow both in number and size quickly and infinitely while maintaining access to a shared dataset. This setup allows for predictable data processing times as additional resources can be provisioned instantly to accommodate spikes in data volume.

Data Pipeline 52

Data Pipeline MongoDB Unstructured Data Data Lake 52

ProjectPro

FEBRUARY 8, 2023

Do ETL and data integration activities seem complex to you? Read this blog to understand everything about AWS Glue that makes it one of the most popular data integration solutions in the industry. Did you know the global big data market will likely reach $268.4 Businesses are leveraging big data now more than ever.

AWS 98

AWS Scala Metadata Data Lake 98

ProjectPro

JANUARY 25, 2022

Here’s What You Need to Know About PySpark This blog will take you through the basics of PySpark, the PySpark architecture, and a few popular PySpark libraries , among other things. Finally, you'll find a list of PySpark projects to help you gain hands-on experience and land an ideal job in Data Science or Big Data.

Big Data 52

Big Data Data Process Process Kafka 52

ProjectPro

JANUARY 6, 2022

However, it might not be ideal for time series data because it requires importing all helper classes for the year, month, week, and day formatters. It's also inconvenient when dealing with several datasets, but converting a dataset into a long format and plotting it is simple. total size of data’).

Python 52

Python Datasets Programming Language Data Science 52

Cloudera

NOVEMBER 13, 2020

This is part of our series of blog posts on recent enhancements to Impala. Apache Impala is synonymous with high-performance processing of extremely large datasets, but what if our data isn’t huge? It turns out that Apache Impala scales down with data just as well as it scales up. The entire collection is available here.

Metadata 143

Metadata Coding SQL Database 143

Rockset

OCTOBER 26, 2022

One was to create another data pipeline that would aggregate data as it was ingested into DynamoDB. After finding Rockset through an AWS blog on creating leaderboards , we wasted no time in starting to build a new customer-facing leaderboard based on Rockset. And that’s true for small datasets and larger ones.

SQL 52

SQL NoSQL Database Aggregated Data 52

AltexSoft

JANUARY 26, 2022

For more detailed information on data science team roles, check our video. An analytics engineer is a modern data team member that is responsible for modeling data to provide clean, accurate datasets so that different users within the company can work with them. Data modeling. What is an analytics engineer?

Engineering 59

Engineering Software Engineering Software Engineer Data Warehouse 59

ProjectPro

AUGUST 24, 2021

Data professionals who work with raw data like data engineers, data analysts, machine learning scientists , and machine learning engineers also play a crucial role in any data science project. And, out of these professions, this blog will discuss the data engineering job role.

Data Engineer 52

Data Engineer Data Engineering Coding Project 52

Confluent

FEBRUARY 6, 2019

The blog posts How to Build and Deploy Scalable Machine Learning in Production with Apache Kafka and Using Apache Kafka to Drive Cutting-Edge Machine Learning describe the benefits of leveraging the Apache Kafka ® ecosystem as a central, scalable and mission-critical nervous system. For now, we’ll focus on Kafka.

Machine Learning 107

Machine Learning Python Kafka Java 107

ProjectPro

NOVEMBER 15, 2021

Table of Contents 20 Open Source Big Data Projects To Contribute How to Contribute to Open Source Big Data Projects? 20 Open Source Big Data Projects To Contribute There are thousands of open-source projects in action today. This blog will walk through the most popular and fascinating open source big data projects.

Big Data 52

Big Data Project Metadata Programming Language 52

ProjectPro

DECEMBER 7, 2021

Data pipelines are a significant part of the big data domain, and every professional working or willing to work in this field must have extensive knowledge of them. A pipeline may include filtering, normalizing, and data consolidation to provide desired data.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Rockset

FEBRUARY 25, 2021

Instead, this data is often semi-structured in JSON or arrays. Often this lack of structure forces developers to spend a lot of their time engineering ETL and data pipelines so that analysts can access the complex datasets. With the many data sources in today’s modern architecture, this can be difficult.

SQL 40

SQL Data Pipeline Kafka Database 40

Rockset

AUGUST 12, 2019

Rockset’s cloud-native architecture allows it to scale query performance and concurrency dynamically as needed, enabling fast queries even on large datasets with complex, nested data with inconsistent types. All that’s left then is to run our queries in our dashboard or application.

NoSQL 40

NoSQL AWS SQL Database 40

Rockset

DECEMBER 22, 2020

There are many blog posts detailing how to build an Express API, I’ll concentrate on what is required on top of this to make calls to Elasticsearch. For Elasticsearch, we have built bespoke functionality to join the datasets together as it isn’t possible natively. To do this we will be using NodeJS to build a simple Express API.

SQL 40

SQL Data MongoDB Building 40

ProjectPro

JULY 27, 2021

This blog is your one-stop solution for the top 100+ Data Engineer Interview Questions and Answers. In this blog, we have collated the frequently asked data engineer interview questions based on tools and technologies that are highly useful for a data engineer in the Big Data industry.

Data Engineer 40

Data Engineer Data Engineering Engineering Hadoop 40

DoorDash Engineering

OCTOBER 17, 2023

Using weights in regression allows efficient scaling of the algorithm, even when interacting with large datasets. With this approach, we don’t just perform the regression computation more efficiently, we also minimize any network transfer costs and latencies and can perform much of the aggregation to get the inputs on the data warehouse.

Education 87

Education Kafka Algorithm Data Warehouse 87

Lyft Engineering

APRIL 21, 2023

In a previous blog post , we explored the architecture and challenges of the platform. In our previous blog , we discussed the various challenges we faced in model monitoring and our strategy to address some of these issues. The profiles are very compact and efficiently describe the dataset with high fidelity.

Systems 105

Systems Building Machine Learning Datasets 105

Cloudera

MARCH 29, 2021

It also provides an advanced materialized view engine to enable live aggregated datasets to be accessible by other applications via a simple REST API. Data decays. Yes, data has a shelf life. This allows users to run continuous queries on data streams over specific time windows. Register NOW!

SQL 115

SQL Scala Manufacturing Java 115

Airbnb Tech

APRIL 30, 2021

While we have previously shared how we ingest data into our data warehouse and how to enable users to conduct their own analyses with contextual data , we have not yet discussed the middle layer: how to properly model and transform data into accurate, analysis-ready datasets. Our work hardly stopped there, however.

Data Warehouse 52

Data Warehouse Finance Metadata Aggregated Data 52

DoorDash Engineering

APRIL 12, 2023

Challenges of ad-hoc SQLs Our initial goal with Curie was to standardize the analysis methodologies and simplify the experiment analysis process for data scientists. After considering the aforementioned factors and studying other existing metric frameworks, we decided to adopt standard BI data models.

SQL 83

SQL Metadata Raw Data Government 83

Rockset

APRIL 15, 2022

This is the second post in a series by Rockset's CTO Dhruba Borthakur on Designing the Next Generation of Data Systems for Real-Time Analytics. We'll be publishing more posts in the series in the near future, so subscribe to our blog so you don't miss them! Both CDC and data enrichment boosted the accuracy and reach of their analytics.

Analytics Application 52

Analytics Application Data Warehouse Kafka Raw Data 52