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Rich data integration and transformation capabilities

Ataccama ONE Big Data Processing & Integration is architected for high performance and scalability, offering rich, built-in features that respond to a range of data transformation needs. Use Ataccama ONE to quickly understand and explore data in your data lake, rapidly process enormous volumes of data, and conduct a detailed data quality analysis before executing necessary transformations.

Use Cases

Data Processing

Perform any kind of transformation, aggregation, or modification while moving data from one data source to another, blend various sources together, or prepare data for further analysis. Reduce data preparation time and increase the efficiency of the discovery process and enjoy elastic computing/big data processing on demand.

Data preprocessing for data engineers, data scientists
& business users

Ataccama ONE includes a number of prebuilt data access and preparation components, a rich GUI for data engineers, and orchestration of integration components. Enjoy data analysis and advanced semantic profiling functionality designed for business users.

Data Lake Profiling, Integration & Data Catalog

Profile, prepare, process, and integrate big data in your data lake. Easily integrate traditional data sources with Hadoop or a data lake to provide seamless data migration as needed, and discover new assets and share your findings in a data catalog.

More Use Cases

Text Analytics & Machine Learning

Use cases include named entities extraction, sentiment analysis, and classification, all supported natively within Hadoop. Integration with Spark 2 MLlib can be used to apply machine learning and text analytics models to your datasets (classification, clustering, regression, and more).

Data Enrichment with External Sources

Easily tap into external data sources to retrieve records. Utilize name, organization, title, and other dictionaries to verify and validate input data. Extend this functionality with customized variables tailored to individual needs.

Real-time & Streaming Integration

Ataccama ONE meets the growing demand for real-time data quality processing, enables users to integrate machine data, and supports IoT and Spark Streaming (Amazon Kinesis, Apache Flume).

Data Quality

Use Ataccama ONE as your main hub for data quality management. Integrate and manage data from all sources in a single platform.

Looking for another use case?


Seamless Migration

Between local and big data environments, as existing configurations can be run on any environment without any changes or need for recompilation.

Data Lake Ready

Integrate, transform and enrich your data with external sources, with support for HDFS, Azure Data Lake Storage, Amazon S3, and other S3 compatible object storages. AWS Glue Data Catalog, Hive, HBase, Kafka, Avro, Parquet, ORC, TXT, CSV, and Excel are also supported.

Support for Elastic Computing/Big Data Processing on Demand

Profile, process, and cleanse your data on automatically provisioned clusters with support for Azure HDInsight, Amazon EMR, Google Dataproc, Databricks, Cloudera, Hortonworks, and MapR clusters. MapReduce, Spark, and Spark 2 engines are utilized.

Hadoop MapReduce and Apache Spark native support

All calculations and processing are executed directly on a cluster, with no need to remove any data from Hadoop. Based on cluster characteristics, the solution is automatically translated into a series of MapReduce jobs, or directly utilizes Spark. Ataccama ONE supports all major Hadoop distributions.

Other Features

Unique Profiling

Enjoy rapid data analysis and advanced semantic profiling functionality.

Support for IoT & Spark Streaming

Including streaming integration with Apache Kafka, Apache NiFi, and Amazon Kinesis.

Advanced Core Functionality

A set of algorithms (capable of hierarchical unification by identifier keys, irrespective of internal data structures) can perform approximate matching during record unification.

Rich Data Integration & Data Preparation Capabilities

For data engineers and data scientists. Profile, asses, transform, and join your datasets in a data lake and in the cloud.

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Customer Success Stories

Discover case studies in your vertical.

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