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

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

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

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

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

Snowflake

JANUARY 29, 2024

Google Analytics, a tool widely used by marketers, provides invaluable insights into website performance, user behavior and critical analytic data that helps marketers understand the customer journey and improve marketing ROI. Your data will now automatically refresh within your Snowflake account based on your preferred frequency.

Raw Data 112

Raw Data Aggregated Data Data Government 112

Snowflake

DECEMBER 6, 2023

While watching a loved one experience a health issue, it became glaringly obvious there was a disconnect in healthcare data and the way providers are able to access and act on it. Every time we had a visit to a primary care physician, an ER trip or a referral to a specialist, data was collected.

Healthcare 94

Healthcare Aggregated Data Medical Data 94

Rockset

OCTOBER 4, 2022

Streaming data feeds many real-time analytics applications, from logistics tracking to real-time personalization. Event streams, such as clickstreams, IoT data and other time series data, are common sources of data into these apps. ClickHouse has several storage engines that can pre-aggregate data.

MySQL 52

MySQL Kafka Aggregated Data Architecture 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

Picnic Engineering

OCTOBER 31, 2023

Datadog aggregates data based on the specific “operations” they are associated with, such as acting as a server, client, RabbitMQ interaction, database query, or various methods. The capability to aggregate data in one place, combined with a wide range of integrations, simplifies data collection and access.

Java 52

Java Aggregated Data Coding Python 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

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

Snowflake

JUNE 8, 2023

Data producers deliver data products from a single source or set of sources, such as data from a CRM application. Those data products could be used by themselves or aggregated into an aggregate data product, like the customer 360 described above. Product thinking works from the outside in.

Aggregated Data 67

Aggregated Data Raw Data Telecommunication Data 67

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

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

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 Cloud Storage SQL 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

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

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

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

AltexSoft

OCTOBER 21, 2022

This scenario involves three main characters — publishers, subscribers, and a message or event broker. A publisher (say, telematics or Internet of Medical Things system) produces data units, also called events or messages , and directs them not to consumers but to a middleware platform — a broker. Kafka cluster and brokers.

Kafka 93

Kafka Hadoop ETL Tools Big Data 93

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

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

Netflix Tech

JULY 12, 2019

Gatekeeper accomplishes its prescribed task by aggregating data from multiple upstream systems, applying some business logic, then producing an output detailing the status of each video in each country. Near : the cache exists in RAM on any instance which requires access to the dataset.

Datasets 73

Datasets Kafka Architecture Aggregated Data 73

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

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

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

AltexSoft

SEPTEMBER 21, 2023

Accessible via a unified API, these new features enhance search relevance and are available on Elastic Cloud. The Elastic Stacks Elasticsearch is integral within analytics stacks, collaborating seamlessly with other tools developed by Elastic to manage the entire data workflow — from ingestion to visualization.

Engineering 52

Engineering NoSQL Programming Language Java 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

Cloudera

NOVEMBER 13, 2020

The reality is that data warehousing contains a large variety of queries both small and large; there are many circumstances where Impala queries small amounts of data; when end users are iterating on a use case, filtering down to a specific time window, working with dimension tables, or pre-aggregated data.

Metadata 143

Metadata Coding SQL Database 143

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

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

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

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