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TimeXtender Data Integration

By leveraging metadata to unify each layer of the data stack and automate manual processes, TimeXtender empowers you to ingest, prepare, and deliver business-ready data 10x faster, while reducing your costs by 70%-80%.

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Ingest, Prepare and Deliver

Build a data infrastructure capable of ingesting, transforming, modeling, and delivering clean, reliable data.

Holistic Data Integration with 3 modular components:

TimeXtender’s modular approach and cloud-based instances give you the freedom to build these components separately (a single data lake, for example), or all together as a complete and integrated data solution.

1.

Ingest Your Data

Consolidate raw data into one, centralized data lake.

2.

Prepare Your Data

Cleanse, validate, enrich, transform, and model the data.

3.

Deliver Your Data

Create data marts that deliver only the relevant subset of data.

Ingest

The Ingestion layer is where TimeXtender consolidates raw data from disconnected sources into one, centralized data lake or lakehouse. This raw data is often used in data science use cases, such as training machine learning models for advanced analytics.

Easily Consolidate Data from Disconnected Sources: Ingest and combine raw data from potentially hundreds of sources into one centralized data lake with minimal effort.
Universal Connectivity: TimeXtender provides a directory of over 250 pre-built, fully-managed data connectors, with additional support for any custom data source.
Automate Ingestion Tasks: Define the scope (which tables) and frequency (the schedule) of data transfers for each of your data sources. By learning from past executions, the Ingestion layer can then automatically set up and maintain object dependencies, optimize data loading, and orchestrate tasks.
Accelerate Data Transfers with Incremental Load: TimeXtender provides the option to load only the data that is newly created or modified, instead of the entire dataset. Because less data is being loaded, you can significantly reduce processing times and accelerate ingestion, validation, and transformation tasks.
No More Broken Pipelines: TimeXtender provides a more intelligent and automated approach to data pipeline management. Whenever a change in your data sources or systems is made, TimeXtender allows you to instantly propagate those changes across the entire pipeline with just a few clicks – no more manually debugging and fixing broken pipelines.

Prepare

The Preparation layer is where you cleanse, validate, enrich, transform, and model the data into a “single version of truth” inside your data warehouse.

Turn Raw Data Into a Single Version of Truth: Select raw data from the Ingestion layer, cleanse, validate, and enrich that data, and then define and execute transformations. Once this data preparation process is complete, you can then map your clean, reliable data into dimensional models to create a “single version of truth” for your organization.
Powerful Data Transformations with Minimal Coding: Whether you’re simply changing a number from positive to negative, or performing complex calculations using many fields in a table, TimeXtender makes the data transformation process simple and easy. All transformations can be performed inside TimeXtender’s low-code user interface, which eliminates the need to write complex code, minimizes the risk of errors, and drastically speeds up the transformation process. These transformations can be made even more powerful when combined with Conditions, Data Selection Rules, and custom code, if needed.
A Modern Approach to Data Modeling: TimeXtender preparation layer empowers you to build a highly structured and organized repository of reliable data to support business intelligence and analytics use cases. It starts with the traditional “star schema”, but adds additional tables and fields that provide valuable insights to data consumers. Because of this, the Preparation layer is easier to understand and use, answers more questions, and is more capable of adapting to change.

Deliver

The Delivery layer provides your entire organization with a simplified, consistent, and business-friendly view of all the data products available to your organization. This Semantic Layer maximizes data discovery and usability, ensures data quality, and aligns technical and non-technical teams around a common data language.

Maximize Data Usability: The Preparation layer can be used to translate technical data jargon into familiar business terms like “product” or “revenue” to create a shared “semantic layer”. This layer provides your entire organization with a simplified, consistent, and business-friendly view of all the data available, which maximizes data discovery and usability, ensures data quality, and aligns technical and non-technical teams around a common data language.
Increase Agility with Data Marts: The Delivery layer allows you to create department or purpose-specific models of your data, often referred to as “data marts”. These data marts provide only the most relevant data to each department or business unit, which means they no longer have to waste time sorting through all the reportable data in the data warehouse to find what they need.
Deploy to Your Choice of Visualization Tools: Semantic models can be deployed to your choice of visualization tools (such as PowerBI, Tableau, or Qlik) for fast creation and flexible modification of dashboards and reports. Because semantic models are created inside TimeXtender, they will always provide consistent fields and figures, regardless of which visualization tool you use. This approach drastically improves data governance, quality, and consistency, ensuring all users are consuming a single version of truth.

Data Users

Intuitive, low-code environment for data transformation and modeling
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Data Movers

Efficiently manage the exploding volume of data
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Business Leaders

Quick access to crucial insights, facilitating more agile and informed decision-making
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IT Leaders

Simplify the integration of new technologies and ensure scalability
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More TimeXtender

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How can we help?

Barry has over 20 years experience as a Data & Analytics architect, developer, trainer and author. He will gladly help you with any questions you may have.

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