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Unlocking Value of Data

BryteFlow unlocks Origin’s large volumes of complex enterprise data (including SAP) making it accessible to functional teams by consolidating all workloads and databases into one powerful engine.

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Real-time Data Integration for S3, Redshift and Snowflake.

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Build a separate Data Lake, Data Warehouse and Data Hub OR get it all in one.

BryteFlow builds the most efficient automated environments for analytics ever. It converts Amazon S3 into an awesome analytics platform by leveraging the AWS ecosystem intelligently to deliver data at lightning speeds. It complements AWS Lake Formation and automates the Modern Data Architecture providing performance and productivity.

Download Ebook: Flip the data switch – Automate Modern Data Architecture on AWS with BryteFlow

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Build an automated, real-time data lake.

BryteFlow provides automated data ingestion with a simple point and click interface that anyone can use. No coding required! Merges data  for data analytics incredibly fast.

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Power business users can model and prepare their data for real-time insights.

BryteFlow automatically merges and remodels data with rich metadata and data lineage from SAP, Oracle, SQL Server and other sources to make it ready for analytics super-fast.

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Access data for a variety of applications.

Whether it is a Relational DW,  relational databases, ML or AI, BryteFlow provides fast access to consistent data across all cloud services for consumption with no impact on source even with multiple users.

We made their data deliver.

Some of our customers who have built efficient analytics environments with BryteFlow.

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Data to Dashboard in minutes!

If you are facing data challenges, get in touch, we can help.

If you are stuck with siloed data that is a pain to extract and load, if data queries seem to take forever, speak to us. We have been troubleshooters to many top global companies
and we would love to help.

Customer Success Stories.

We are data partners to some of the biggest names in business. Read our success stories to find out why we have built a loyal following.

More Success Stories

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Origin Energy
Unlocked large volumes of complex enterprise data including SAP.

Origin data is now accessible to functional teams across the organization consolidating all workloads and databases into one powerful engine.

READ MORE
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Vocus Communications
Vocus reduced data deployment time by 75%

Vocus Communications new analytics environment took just 3 months to build – reducing data deployment time by 75%!

READ MORE
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ANZ Bank
ANZ gets market insights delivered 10x faster than before.

BryteFlow's data solution powers ANZ's high performance Market Analysis and Predictive Analytics engine at mach speed.

READ MORE

Why BryteFlow?

How BryteFlow's revolutionary technology makes sound financial sense.

How BryteFlow Works

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Data extracted, loaded and prepared in real time. No waiting!

Access data insights that much faster to dominate the market.
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High concurrency: your entire team can query at the same time without slowing down of the source system.

Save on resource time.Analytics and operations can both work independently.
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Bryteflow separates your storage and compute processes.

You pay only for processing. Storage is crazy-cheap!
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Load any data, from any data source like SAP, Oracle, SQL Server etc. into S3, and Azure Blob.

Free your trapped data from its silo and use it easily.
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Data gets continuously synced with tables in database so you have the latest version.

Your data is always verified and current so it is 100% accurate.
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No coding needed with the easy point and click BryteFlow interface.

No need for expensive tech hires. Just about anyone can use BryteFlow.

Browse

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EBOOK
Optimizing your Enterprise Data Management

Tips on how you can convert your data
environment into an analyst's paradise.

Download the Ebook

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Headache points – Liberating your data from SAP, Oracle, SQL Server and other complex application environments.

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WEBINAR

Data Insights Super Fast: AWS | Bryte Data Lake Strategy

View

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POST

What is Schema-on-Read and how does it differ from Schema-on-Write?

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