AWS Big Data

AUGUST 19, 2024

As organizations increasingly rely on data stored across various platforms, such as Snowflake , Amazon Simple Storage Service (Amazon S3), and various software as a service (SaaS) applications, the challenge of bringing these disparate data sources together has never been more pressing. For more information on AWS Glue, visit AWS Glue.

Analytics 119

Analytics Data-driven Data Integration Data Lake 119

Jet Global

MAY 27, 2022

Synapse services are powerful tools for bringing data together for analytics, machine learning, reporting needs, and more. How Synapse works with Data Lakes and Warehouses. Synapse services, data lakes, and data warehouses are often discussed together. Streamline Data with Atlas. Book A Demo.

Data Lake 52

Data Lake IT Recreation/Entertainment Data Warehouse 52

AWS Big Data

JULY 13, 2023

Generating business outcomes In 4 days, the Altron SI team left the Immersion Day workshop with the following: A data pipeline ingesting data from 21 sources (SQL tables and files) and combining them into three mastered and harmonized views that are cataloged for Altron’s B2B accounts.

Optimization 98

Optimization B2B Data Quality Sales 98

IBM Big Data Hub

DECEMBER 16, 2022

You have a specific book in mind, but you have no idea where to find it. You enter the title of the book into the computer and the library’s digital inventory system tells you the exact section and aisle where the book is located. It uses metadata and data management tools to organize all data assets within your organization.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

Jet Global

JANUARY 30, 2025

Its distributed architecture empowers organizations to query massive datasets across databases, data lakes, and cloud platforms with speed and reliability. Optimizing connections to your data sources is equally important, as it directly impacts the speed and efficiency of data access.

Data Lake 64

Data Lake Data-driven Optimization Enterprise 64

Jet Global

MAY 9, 2024

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

Jet Global

FEBRUARY 23, 2024

Data mapping is essential for integration, migration, and transformation of different data sets; it allows you to improve your data quality by preventing duplications and redundancies in your data fields. Data mapping helps standardize, visualize, and understand data across different systems and applications.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Visualization 52

Jet Global

JUNE 13, 2022

When migrating to the cloud, there are a variety of different approaches you can take to maintain your data strategy. Those options include: Data lake or Azure Data Lake Services (ADLS) is Microsoft’s new data solution, which provides unstructured date analytics through AI. Different Approaches to Migration.

Reporting 52

Reporting Data Lake Sales Operational Reporting 52

Jet Global

APRIL 26, 2022

For companies that operate multiple corporate entities, the most common approach is to create distinct companies within D365 F&SCM, each with its own set of books. Jet Reports now offers high performance connectivity with options to connect to Synapse/Azure Data Lakes, BYOD, SQL or your Cubes and Tabular models.

Reporting 52

Reporting Finance Cost-Benefit Forecasting 52

Jet Global

SEPTEMBER 30, 2022

What are the best practices for analyzing cloud ERP data? Data Management. How do we create a data warehouse or data lake in the cloud using our cloud ERP? How do I access the legacy data from my previous ERP? How can we rapidly build BI reports on cloud ERP data without any help from IT?

Reporting 52

Reporting Data Warehouse Operational Reporting Enterprise 52

Jet Global

MARCH 27, 2025

Indeed, the transition is not merely a trend but a reality rooted in the need for enhanced flexibility, scalability, and data integration capabilities not sufficiently provided by SAP BPC. data lakes & warehouses like Cloudera, Google Big Query, etc., This includes databases like Microsoft SQL server, IBM DB2, etc.,

Finance 52

Finance Reporting Cost-Benefit Forecasting 52