Lyft Engineering

NOVEMBER 29, 2023

Our initial use for Druid was for near real-time geospatial querying and high performance on high-cardinality data sets. It also allowed us to optimize for handling time-series data and event data at scale. Pre-aggregating data at ingestion time helped optimize our query performance and reduce our storage costs.

Kafka 104

Kafka Data Ingestion Datasets Architecture 104

LinkedIn Engineering

DECEMBER 19, 2023

Our RU framework ensures that our big data infrastructure, which consists of over 55,000 hosts and 20 clusters holding exabytes of data, is deployed and updated smoothly by minimizing downtime and avoiding performance degradation. Accessibility of all namenodes. No concurrent upgrades are happening within the cluster.

Big Data 92

Big Data Hadoop Metadata Data 92

Rockset

AUGUST 25, 2021

It’s simply too expensive to store all the raw data and simply too slow to run batch processes to pre-aggregate it. One common example is a mobile app, where every activity is recorded as an event, resulting in millions of events per day streaming in.

Aggregated Data 52

Aggregated Data Data Lake Hadoop SQL 52

ProjectPro

FEBRUARY 8, 2023

Application programming interfaces (APIs) are used to modify the retrieved data set for integration and to support users in keeping track of all the jobs. Users can schedule ETL jobs, and they can also choose the events that will trigger them. Create schedules or events that will act as job triggers.

AWS 98

AWS Scala Metadata Data Lake 98

DoorDash Engineering

APRIL 12, 2023

Additionally, having a centralized repository of metrics facilitates easy access to metrics, empowering all members of an organization to analyze experiment results. Data scientists are the primary metric creators and are already familiar with SQL, so it made sense to use SQL as the language to define metrics instead of building our own DSL.

SQL 82

SQL Metadata Raw Data Government 82

DareData

JULY 5, 2023

The Data Lake acts as the central repository for aggregating data from diverse sources in its raw format. Typically, it is advisable to retain the data in its original, unaltered format when transferring it from any source to the data lake layer.

Data Lake 52

Data Lake Building Raw Data ETL Tools 52

Knowledge Hut

JANUARY 3, 2024

After thoroughly examining each circumstance, they will share any new knowledge obtained about current cyber threats or vulnerabilities inside their network so that future events can be avoided, if possible, by immediate fixes. Essential compliance consists of access to patch levels, threat information, identity, and data access control.

Computer Science 52

Computer Science Certification Data Mining Data Security 52

Rockset

AUGUST 30, 2021

It eliminates the cost and complexity around data preparation, performance tuning and operations, helping to accelerate the movement from batch to real-time analytics. The latest Rockset release, SQL-based rollups, has made real-time analytics on streaming data a lot more affordable and accessible.

SQL 52

SQL Kafka MongoDB MySQL 52

Rockset

MARCH 1, 2023

In addition, Rockset provides fast data access through the use of more performant hot storage, while cloud storage is used for durability. Then, I used the integration to create a collection, twitter_kinesis_30day , that syncs Twitter data from the Kinesis stream.

Architecture 59

Architecture AWS SQL Cloud Storage 59

Picnic Engineering

SEPTEMBER 8, 2022

Quick re-cap: the purpose of the internal pipeline is to deliver data from dozens of Picnic back-end services such as warehousing, machine learning models, customers and order status updates. The data is loaded into Snowflake, Picnic’s single source of truth Data Warehouse (DWH). Yet, some messages are destined for the DWH only.

Kafka 52

Kafka Metadata AWS Java 52

Rockset

APRIL 15, 2022

It’s probably because their analytics database lacks the features necessary to deliver data-driven decisions accurately in real time. It’s probably because their analytics database lacks the features necessary to deliver data-driven decisions accurately in real time. Transmitting out-of-order data is not the issue.

Analytics Application 52

Analytics Application Data Warehouse Raw Data Kafka 52

Knowledge Hut

OCTOBER 13, 2023

Aggregate Data: If you don't need granularity, consider aggregating data before loading it into Power BI to reduce the volume of data. Sort and Filter Early: Apply sorting and filtering in your queries as early as possible to reduce the amount of data transferred and processed.

BI 52

BI Business Analyst Datasets Raw Data 52

Rockset

NOVEMBER 1, 2022

Step 1: Data Acquisition Elasticsearch is rarely the system of record which means the data in it comes from somewhere else for real-time analytics. Rockset has built-in connectors to stream real-time data for testing and simulating production workloads including Apache Kafka , Kinesis and Event Hubs.

Database-centric 52

Database-centric Pipeline-centric SQL Aggregated Data 52

DoorDash Engineering

OCTOBER 17, 2023

Experiment exposures are one of our highest volume events. On a typical day, our platform produces between 80 billion and 110 billion exposure events. We stream these events to Kafka and then store them in Snowflake. Users can query this data to troubleshoot their experiments. Below are sample charts from our dashboards.

Education 87

Education Kafka Algorithm Data Warehouse 87

Ascend.io

SEPTEMBER 14, 2023

We’ll explore its advantages, delve into its applications, and highlight why Python is increasingly becoming the first choice for data engineers worldwide. Why Python for Data Engineering? As the field of data engineering evolves, the need for a versatile, performant, and easily accessible language becomes paramount.

Data Engineering 52

Data Engineering Data Engineer Python Engineering 52

Databand.ai

JULY 10, 2023

This includes integration with common data sources, incident management systems, ticketing systems, CI/CD tools, and more, further streamlining the process of identifying and resolving issues. Security: Observability platforms often include built-in security features to ensure the integrity and confidentiality of your data.

Data Pipeline 52

Data Pipeline Algorithm Raw Data Aggregated Data 52

Scott Logic

JULY 26, 2023

Knowledge Graphs, to quote the Alan Turing Institute , “organise data from multiple sources, capture information about entities of interest in a given domain or task (like people, places or events), and forge connections between them.” It was hypothesised that in combination with the Knowledge Graph, the LLM (e.g.

Banking 52

Banking Aggregated Data Retail Architecture 52

Knowledge Hut

NOVEMBER 17, 2023

To be an Azure Data Engineer, you must have a working knowledge of SQL (Structured Query Language), which is used to extract and manipulate data from relational databases. You should be able to create intricate queries that use subqueries, join numerous tables, and aggregate data.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

ProjectPro

JANUARY 25, 2022

PySpark allows you to process data from Hadoop HDFS , AWS S3, and various other file systems. Get FREE Access to Data Analytics Example Codes for Data Cleaning, Data Munging, and Data Visualization The PySpark Architecture The PySpark architecture consists of various parts such as Spark Conf, RDDs, Spark Context, Dataframes , etc.

Big Data 52

Big Data Data Process Process Kafka 52

Knowledge Hut

SEPTEMBER 27, 2023

Example: Imagine that your team is analyzing sales data for an internet consumer company with millions of transactions that happen weekly. QuickSight's SPICE engine stores the aggregated data in memory, allowing very fast query response times.

BI 52

BI AWS Database-centric Data Lake 52

Airbnb Tech

APRIL 30, 2021

Minerva takes fact and dimension tables as inputs, performs data denormalization, and serves the aggregated data to downstream applications. Flexible Backfills: Minerva version controls data definitions, so major changes to the datasets are automatically tracked and backfilled.

Data Warehouse 52

Data Warehouse Finance Metadata Aggregated Data 52

Confluent

FEBRUARY 6, 2019

The data scientist “just” deploys its trained model, and production engineers can access it. While all these solutions help data scientists, data engineers and production engineers to work better together, there are underlying challenges within the hidden debts: Data collection (i.e.,

Machine Learning 106

Machine Learning Python Kafka Java 106

ProjectPro

DECEMBER 7, 2021

The second step for building etl pipelines is data transformation, which entails converting the raw data into the format required by the end-application. The transformed data is then placed into the destination data warehouse or data lake. It can also be made accessible as an API and distributed to stakeholders.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

phData: Data Engineering

JANUARY 3, 2022

The big data analytics market is set to reach $103 billion by 2023 , with poor data quality costing the US economy up to $3.1 Fortune 1000 companies can gain more than $65 million additional net income, only by increasing their data accessibility by 10%. What is Data Governance? trillion yearly.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52

LinkedIn Engineering

DECEMBER 20, 2023

This includes taking measures such as issuing warnings, restricting access, or suspending accounts as necessary. The feedback loop serves as a critical component of a dynamic defense strategy, constantly monitoring and aggregating data from abuse reports, member feedback, and reviewer input.

Building 91

Building Algorithm Kafka Machine Learning 91

ProjectPro

NOVEMBER 15, 2021

When any particular project is open-sourced, it makes the source code accessible to anyone. The adaptability and technical superiority of such open-source big data projects make them stand out for community use. It serves as a distributed processing engine for both categories of data streams: unbounded and bounded.

Big Data 52

Big Data Project Metadata Programming Language 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. Rockset supports full-featured SQL, enabling filtering, sorting, aggregating, and joining data in SQL.

SQL 40

SQL Data Pipeline Kafka Database 40

ProjectPro

OCTOBER 28, 2015

The aim of selecting an ETL tool is to ensure that data is moving into Hadoop at a frequency that can meet the analytic requirements. Sqoop vs Flume-Comparison of the two Best Data Ingestion Tools Get FREE Access to Data Analytics Example Codes for Data Cleaning, Data Munging, and Data Visualization What is Sqoop in Hadoop?

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

ProjectPro

OCTOBER 29, 2021

Before moving on to the steps to improve data quality, let us spend a moment in this section to understand just what it is we seek to change. Accuracy Accuracy refers to how well the information recorded reflects a real event or object. Nonparametric.

Data Mining 52

Data Mining Datasets Machine Learning Metadata 52

ProjectPro

AUGUST 24, 2021

Data Engineering Project for Beginners If you are a newbie in data engineering and are interested in exploring real-world data engineering projects, check out the list of data engineering project examples below. This big data project discusses IoT architecture with a sample use case.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Rockset

AUGUST 12, 2019

As an example, let’s say we are organizing a charity fundraiser and want a live dashboard at the event to show the progress towards our fundraising goal. After creating an account at www.rockset.com , we’ll use the console to set up our first integration– a set of credentials used to access our data.

NoSQL 40

NoSQL AWS SQL Datasets 40

ProjectPro

JULY 27, 2021

You may add new data regularly, but once you add the data, it does not change very frequently. Data is regularly updated. Data warehouses are optimized to handle complex queries, which can access multiple rows across many tables. There is a large amount of data involved. The amount of data is usually less.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

JUNE 28, 2016

Get FREE Access to Data Analytics Example Codes for Data Cleaning, Data Munging, and Data Visualization What Kafka does? Kafka is extensively being used across industries for general – purpose messaging system where high availability and real time data integration and analytics are of utmost importance.

Kafka 40

Kafka Systems Hadoop BI 40

ProjectPro

FEBRUARY 22, 2022

Get FREE Access to Data Analytics Example Codes for Data Cleaning, Data Munging, and Data Visualization European Soccer Game Analysis If you are a soccer fan and enjoy analyzing trends in sports teams, this project is for you. League: It contains the specific titles of the sports events/league matches.

Data Analysis 52

Data Analysis SQL Project Banking 52

Cloudera

JUNE 29, 2023

Incorporate data from novel sources — social media feeds, alternative credit histories (utility and rental payments), geo-spatial systems, and IoT streams — into liquidity risk models. Use cases include: Enable transparent access to financial data. Possible applications include: Improved customer risk profiling.

Data Architecture 83

Data Architecture Architecture Management Banking 83

AltexSoft

DECEMBER 23, 2022

In ELT, raw data is loaded into the destination, and then it receives transformations when it’s needed. Organizations now operate huge amounts of various data stored in multiple systems. ELT makes it easier to manage and access all this information by allowing both raw and cleaned data to be loaded and stored for further analysis.

Process 52

Process Building Raw Data Data Lake 52

U-Next

SEPTEMBER 7, 2022

The terms “ Data Warehouse ” and “ Data Lake ” may have confused you, and you have some questions. In the event that they are not the same, what are the difference s? The DW and databases support multi-user access. In order to access the data, both the DW and the database require queries.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 52