Remove Data Processing Remove Data Warehouse Remove Metadata Remove Reporting
article thumbnail

How smava makes loans transparent and affordable using Amazon Redshift Serverless

AWS Big Data

The data products used inside the company include insights from user journeys, operational reports, and marketing campaign results, among others. The data platform serves on average 60 thousand queries per day. The data volume is in double-digit TBs with steady growth as business and data sources evolve.

article thumbnail

Create an end-to-end data strategy for Customer 360 on AWS

AWS Big Data

Without C360, businesses face missed opportunities, inaccurate reports, and disjointed customer experiences, leading to customer churn. Profile aggregation – When you’ve uniquely identified a customer, you can build applications in Managed Service for Apache Flink to consolidate all their metadata, from name to interaction history.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Enhance monitoring and debugging for AWS Glue jobs using new job observability metrics, Part 3: Visualization and trend analysis using Amazon QuickSight

AWS Big Data

QuickSight makes it straightforward for business users to visualize data in interactive dashboards and reports. You can slice data by different dimensions like job name, see anomalies, and share reports securely across your organization. QuickSight lets you perform aggregate calculations on metrics for deeper analysis.

Metrics 101
article thumbnail

What is Data Mapping?

Jet Global

Data sources are crucial for reporting, analyzing, and acting on transactional and corporate data and connecting these sources in real time with various tools like connectors, ETL tools, mashups, Web services, and data source-neutral BI solutions is essential. Data warehouses can be complex, time-consuming, and expensive.

article thumbnail

Build a serverless transactional data lake with Apache Iceberg, Amazon EMR Serverless, and Amazon Athena

AWS Big Data

They enable transactions on top of data lakes and can simplify data storage, management, ingestion, and processing. These transactional data lakes combine features from both the data lake and the data warehouse. Data can be organized into three different zones, as shown in the following figure.

article thumbnail

Extreme data center pressure? Burst to the cloud with CDP!

Cloudera

At these times, they run business growth reports, shareholder reports, and financial reports for their earnings calls, to name a few examples. Cloud deployments for suitable workloads gives you the agility to keep pace with rapidly changing business and data needs. How Burst to Cloud can solve your data center pressure.

article thumbnail

Why Enterprise Data Lineage is Critical for the Success of Your Modern Data Stack

Octopai

The modern data stack is a data management system built out of cloud-based data systems. A given modern data stack will usually include components for data ingestion from your data sources, data transformation, data storage, data analysis and reporting.