Big Data Management

Big data platforms and data lakes accumulate vast amounts of data. This data is usually not as well-structured and understood as the data produced by traditional data integration processes and stored in data warehouses. As a result, providing, finding, and protecting this data requires advanced data management technology.

image/svg+xml 94% 94 59 59% 30% 11% consider data governanceimportant or essential forbig data1. use two or more clouds forstorage, processing, andanalytics3. have a dedicated dataquality team2. use data quality toolswidely across theorganization2. and but only and at the same time Limited resources Lots of scattered data Untitled 94% consider data governance important or essential for big data 1 . 30% have a dedicated data quality team 2 . 11% use data quality tools widely across the organization 2 . 59% use two or more clouds for storage, processing, and analytics 3 . and at the same time but only and

The consequences of ungoverned big data are dire.


Data swamps

Data lakes turn into data swamps, leading to wasted storage costs and underutilization of data.


Lack of data security

Data protection and privacy are even more complicated than in traditional data environments.


Lack of understanding

Data people lack data discovery tools and waste time finding data, understanding it, and preparing it.


Poor data quality

Data people cannot trust the data and data engineers are constantly under pressure to fix data pipelines.


Complicated data source onboarding

Duplicate and complicated configuration of data quality transformations for each new data source.

Successful big data management includes data discovery, standardization and cleansing, self-service access to data, data preparation, and support for stream processing.

Discover your whole data lake and protect sensitive information

Ensure data quality on any data volume, reliably and without code

Best of all, run processing directly on the data lake

Ataccama ONE integrates with industry-leading big data clusters to ensure parallel and scalable data processing, including streaming.

At the same time, your data stays in the data lake and your organization stays compliant with data residency regulations.

Best of all, run processing directly on the data lake

Here is how enterprises harness big data with Ataccama

1.5 billion records in 99 seconds

That’s how fast X5 Retail Group check product master data on demand on their data lake for product innovation

Millions in unpaid balances

That’s how much First Data (now Fiserv) uncovered thanks to data cleansing and enrichment in the PoC phase.

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110 billion records

That’s the size of data that this American F&B retailer processes with Databricks on Azure Data Lake and catalogs in the Ataccama ONE Data Catalog.

2 person days a week

That’s how much analyst and DevOps time this American F&B retailer saves thanks to automated cataloging and monitoring of their data lake.

All the tools for data governance in ONE platform

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Big Data Management Resources

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 4 Reasons Your Data Lake Needs a Data Catalog

4 Reasons Your Data Lake Needs a Data Catalog

Data lakes contain several deficiencies and bring about data…

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Ataccama ONE is a full stack data management platform.
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