This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
Introducing the SFTP connector for AWS Glue The SFTP connector for AWS Glue simplifies the process of connecting AWS Glue jobs to extract data from SFTP storage and to load data into SFTP storage. Solution overview In this example, you use AWS Glue Studio to connect to an SFTP server, then enrich that data and upload it to Amazon S3.
The Data Platform team is responsible for supporting data-driven decisions at smava by providing data products across all departments and branches of the company. The departments include teams from engineering to sales and marketing. The data platform serves on average 60 thousand queries per day.
Net sales of $386 billion in 2021 200 million Amazon Prime members worldwide Salesforce As the leader in sales tracking, Salesforce takes great advantage of the latest and greatest in analytics. They take their reports and showcase them through an instantaneous visualization on record pages.
Unlocking the full potential of your data is about more than just visualizing it. True datatransformation comes from applying insights to make impactful business decisions.
This field guide to data mapping will explore how data mapping connects volumes of data for enhanced decision-making. Why Data Mapping is Important Data mapping is a critical element of any data management initiative, such as data integration, data migration, datatransformation, data warehousing, or automation.
Data Extraction : The process of gathering data from disparate sources, each of which may have its own schema defining the structure and format of the data and making it available for processing. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.
Thorough data preparation and control act as the foundation, allowing finance teams to leverage the full power of Oracle’s AI and transform their financial operations, now or in the future. Imagine this: salesdata in your CRM uses opportunity IDs, while your ERP system uses unique sales order numbers.
Trino allows users to run ad hoc queries across massive datasets, making real-time decision-making a reality without needing extensive datatransformations. This is particularly valuable for teams that require instant answers from their data. Data Lake Analytics: Trino doesn’t just stop at databases.
However, leveraging these insights can be challenging if your reports and data don’t speak to each other. Disconnected enterprise performance management (EPM) operationalreporting can present significant limitations and challenges for your business. Transforming Financial Reporting with Dynamic Dashboards Download Now 1.
Complex Data Structures and Integration Processes Dynamics data structures are already complex – finance teams navigating Dynamics data frequently require IT department support to complete their routine reporting.
By providing a consistent and stable backend, Apache Iceberg ensures that data remains immutable and query performance is optimized, thus enabling businesses to trust and rely on their BI tools for critical insights. It provides a stable schema, supports complex datatransformations, and ensures atomic operations.
We organize all of the trending information in your field so you don't have to. Join 42,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content