Knowledge Hut

APRIL 19, 2023

The process of merging and summarizing data from various sources in order to generate insightful conclusions is known as data aggregation. The purpose of data aggregation is to make it easier to analyze and interpret large amounts of data. Let's look at the use case of data aggregation below.

Process 59

Process Data Mining Aggregated Data Portfolio 59

Uber Engineering

JANUARY 15, 2020

Uber leverages real-time analytics on aggregate data to improve the user experience across our products, from fighting fraudulent behavior on Uber Eats to forecasting demand on our platform. .

SQL 112

SQL Engineering Aggregated Data Hadoop 112

Cloudyard

JUNE 11, 2024

This pipeline consists of several sequential tasks: Task A: Loads raw data into a staging table. Task B: Transforms the data in the staging table. Task C: Aggregates the transformed data (simulates a potential failure). Task D: Loads the aggregated data into the final table.

Raw Data 52

Raw Data Aggregated Data Data Pipeline Data Workflow 52

Striim

JULY 31, 2024

Why Striim Stands Out As detailed in the GigaOm Radar Report, Striim’s unified data integration and streaming service platform excels due to its distributed, in-memory architecture that extensively utilizes SQL for essential operations such as transforming, filtering, enriching, and aggregating data.

Aggregated Data 52

Aggregated Data Data Ingestion Java Kafka 52

Confluent

OCTOBER 25, 2022

Joining two topics to aggregate data is fundamental in stream processing, but it’s not easy. Learn how to use kcat to debug and ensure two topics use the same keys in the same partitions.

Aggregated Data 52

Aggregated Data Process 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 72

Aggregated Data Raw Data Telecommunication Data 72

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

MARCH 3, 2023

As a CDO, I need full data life cycle capability. I must store data efficiently and resiliently, pipe and aggregate data into data lakehouses, and apply machine learning algorithms and AI to uncover actionable insights for our business units. But I have good reasons to prefer CDP! First, fullness. Second, reach.

Aggregated Data 83

Aggregated Data Consulting Government AWS 83

Ascend.io

OCTOBER 28, 2024

Intermediate Data Transformation Techniques Data engineers often find themselves in the thick of transforming data into formats that are not only usable but also insightful. Intermediate data transformation techniques are where the magic truly begins.

Raw Data 52

Raw Data Datasets Aggregated Data Data Pipeline 52

KDnuggets

AUGUST 6, 2019

Check out this video (and Jupyter notebook) which outlines a number of Pandas tricks for working with and manipulating data, covering topics such as string manipulations, splitting and filtering DataFrames, combining and aggregating data, and more.

Aggregated Data 95

Aggregated Data Data Python 95

Data Engineering Weekly

SEPTEMBER 26, 2024

Silver Layer: In this zone, data undergoes cleaning, transformation, and enrichment, becoming suitable for analytics and reporting. Access expands to data analysts and scientists, though sensitive elements should remain masked or anonymized. It's accessible to a wider audience, including business users and BI tools.

Systems 67

Systems Engineering Data Warehouse Architecture 67

Monte Carlo

NOVEMBER 11, 2024

For this organization, that behavior change started when the data team aggregated data quality incidents and the impact of their resolution. Data producers and consumers realized] they wouldn’t have to clean up the data every month because Monte Carlo had already prevented the issue.

Data 52

Data Aggregated Data Data Governance Data Engineer 52

Striim

APRIL 3, 2024

Traditionally, this involves aggregating data from multiple sources such as HubSpot and Zendesk, a process that is both time-consuming and requires extensive technical expertise.

Google Cloud 52

Google Cloud Transportation Data Integration Aggregated Data 52

Cloudera

JUNE 29, 2023

Streamline KYC and AML, too While Know Your Customer (KYC) and Anti-Money-Laundering (AML) processes didn’t play a role in the recent collapses, institutions can also leverage the combination of a modern, open data architecture, advanced analytics, and machine automation to transform KYC and AML.

Data Architecture 84

Data Architecture Architecture Management Banking 84

Cloudera

OCTOBER 11, 2022

Most AI apps and ML models need different types of data – real-time data from devices, equipment, and assets and traditional enterprise data – operational, customer, service records. . But it isn’t just aggregating data for models. Data needs to be prepared and analyzed.

Data Science 93

Data Science Aggregated Data Data Consulting 93

Rockset

AUGUST 25, 2021

Instead, if you can “rollup” data as it is being generated, then you can define metrics that can be tracked in real time across a number of dimensions with better performance and lower cost. This greatly reduces both the amount of data stored and the compute for queries.

Aggregated Data 52

Aggregated Data Hadoop SQL Data Lake 52

Snowflake

APRIL 9, 2024

Using data to coach and support sales development reps For the SDR leadership team, having information that’s trusted, accessible and available in near real time means they can make truly data-driven management decisions.

BI 79

BI Data Ingestion Data Aggregated Data 79

Knowledge Hut

JANUARY 19, 2024

New Analytics Strategy vs. Existing Analytics Strategy Business Intelligence is concerned with aggregated data collected from various sources (like databases) and analyzed for insights about a business' performance. In contrast, Business Analytics involves an analytical approach to solving problems within a business context.

Business Intelligence 52

Business Intelligence BI Business Analyst Aggregated Data 52

WeCloudData

OCTOBER 19, 2021

Furthermore, one cannot combine and aggregate data from publicly available job boards into custom graphs or dashboards. The client needed to build its own internal data pipeline with enough flexibility to meet the business requirements for a job market analysis platform & dashboard.

Consulting 52

Consulting Raw Data Data Lake Data Pipeline 52

WeCloudData

OCTOBER 19, 2021

Furthermore, one cannot combine and aggregate data from publicly available job boards into custom graphs or dashboards. The client needed to build its own internal data pipeline with enough flexibility to meet the business requirements for a job market analysis platform & dashboard.

Consulting 52

Consulting Raw Data Data Lake Data Pipeline 52

Snowflake

OCTOBER 16, 2023

Data needs in human services Efficient, centralized technologies are indispensable when addressing basic human needs like food and shelter as well as general social welfare.

Healthcare 82

Healthcare Programming Hospitality Food 82

Rockset

OCTOBER 4, 2022

Ingest Transformations and Rollups It is useful to be able to transform and rollup streaming data as it is being ingested. ClickHouse has several storage engines that can pre-aggregate data. Rollups in Rockset are a special type of transformation that aggregates data upon ingest.

MySQL 52

MySQL Kafka Aggregated Data Architecture 52

Snowflake

JUNE 22, 2023

These aggregate data products combine multiple building blocks. Some also talk about aggregate data products. As the name suggests, these products aggregate multiple data products, often an intermediate step between multiple sources and the consumer.

Building 52

Building Business Analyst Aggregated Data Data 52

Towards Data Science

FEBRUARY 9, 2023

This allows me to load this data incrementally. I will go over the raw data to load the day, go over the daily aggregated data to load the month, and finally through the daily data to update the counts for the user that have changed.

Big Data 82

Big Data Raw Data Aggregated Data Data 82

Striim

APRIL 4, 2024

Traditionally, this involves aggregating data from multiple sources such as Zendesk and Hubspot, a process that is both time-consuming and requires extensive technical expertise.

Transportation 40

Transportation Google Cloud Aggregated Data Cloud 40

Edureka

AUGUST 19, 2024

It will help to detect an issue fast and solve it right before the end-users are affected by aggregating data on application behavior. Tools like AppDynamics, Instana, New Relic, Jaeger, OpenTracing measure and thus analyze application metrics, which in turn aid in solving problems before they reach the end-users.

Engineering 98

Engineering Programming Language Python Cloud 98

Knowledge Hut

JANUARY 25, 2024

Encoding categorical variables, scaling numerical features, creating new features, aggregating data. One-hot encoding categorical variables, standardizing numerical features, aggregating data. Outcome A cleaner, more accurate dataset. A modified dataset suitable for analysis or modeling.

Data Cleanse 52

Data Cleanse Datasets Data Preparation Data Science 52

LinkedIn Engineering

OCTOBER 13, 2023

We were able to stack data side by side to compare directly in our platform as opposed to exporting everything from its source system and manually normalizing the data to start comparison.

Management 98

Management IT Aggregated Data Programming 98

Monte Carlo

FEBRUARY 15, 2023

Pay only for the resources used at that point in time Central repository (Single source of truth) Data from multiple sources are migrated into data warehouses They are cleaned, transformed, and aggregated to derive insights Business Intelligence tools like Sisense data and Tableau are plugged on top of aggregated data Aggregated data are also fed into (..)

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

Precisely

MARCH 12, 2024

How does data enrichment work? Automating address corrections and updates , for example, increases accuracy, saves money, and improves customer satisfaction.

Insurance 52

Insurance Telecommunication Retail High Quality Data 52

Cloudera

FEBRUARY 16, 2021

Integrated across the Enterprise Data Lifecycle . Cloudera Operational Database (COD) plays the crucial role of a data store in the enterprise data lifecycle. You can use COD with: Cloudera DataFlow to ingest and aggregate data from various sources. Cloudera Data Warehouse to perform ETL operations.

Database 81

Database Machine Learning Kafka Aggregated Data 81

Knowledge Hut

APRIL 23, 2024

The processing and analysis of big data require specialized tools and technologies. Data mining techniques can be applied using conventional computing resources. Data mining analysis employs clustering, classification, regression, association rules, and anomaly detection algorithms.

Data Mining 52

Data Mining Big Data Database-centric Unstructured Data 52

Rockset

AUGUST 30, 2021

You can also optionally use WHERE clauses to filter out data. Since only the aggregated data is now ingested and indexed into Rockset, this technique reduces the compute and storage required to track real-time metrics by a few orders of magnitude.

SQL 52

SQL Kafka MongoDB MySQL 52

Netflix Tech

NOVEMBER 20, 2023

Instead of overwriting past X days of data completely by using a lookback window pattern, user workflows just need to MERGE the change data (including late arriving data) into the target table by processing the ICDC table.

Process 86

Process Data Pipeline Datasets SQL 86

Cloudera

FEBRUARY 9, 2023

The sudden failing of a complex data pipeline can lead to devastating consequences — especially if it goes unnoticed. This is why we build job notifications functionality into SSB, to deliver maximum reliability in your complex real-time data pipelines.

SQL 77

SQL Kafka Aggregated Data Architecture 77

Precisely

APRIL 6, 2023

Twenty years ago, top-performing organizations were using “extract, transform, load” (ETL) processes to normalize and aggregate data for business analytics. The end result is inefficiency in the organization’s operational processes.

Data Integration 52

Data Integration Aggregated Data Data Pipeline Cloud Computing 52

Striim

JULY 10, 2024

Data transformation includes normalizing data, encoding categorical variables, and aggregating data at the appropriate granularity. Cleaning involves removing duplicates, handling missing values, and correcting errors. The next phase is model development.

Management 52

Management Transportation Machine Learning High Quality Data 52