Datastreamer

Score7.3 out of 10

1 Reviews and Ratings

What is Datastreamer?

Datastreamer is turnkey data platform to source, unify, and enrich unstructured data with less work than building data pipelines in-house.

Traditional ETL processes and pipelines might not meet the needs of organizations who want to implement unstructured and semi-structured sources such as external social media, blogs, news, forums, and dark web data into their products. This leaves data teams to build pipelines internally which comes with time-draining technical complexities and prohibitive costs. Datastreamer aims to solve the gap between data suppliers and data consumers by transforming unstructured web data into an enriched, structured format that accelerates analytics.

Customers use Datastreamer to save hours of work for analysts in Threat Intelligence, Media Monitoring, and KYC/AML.

Scale with Less Operating Costs
The vendor states that a Datastreamer customer saves 3-6 months of time and $750k/year compared to building data pipelines in house. The solution helps to accelerate the user's roadmap by eliminating the most time-consuming aspects of data ingestion, and minimize data ingestion costs by plugging into a managed infrastructure that is optimized to handle massive volumes of text data.

Source & Unify Data
Billions of data points can be accessed with Datastreamer's pre-integrated data partners or the user's own data sources can be connected. Datastreamer unifies source data into a common schema that can be used from multiple sources simultaneously.

Enhanced Data with AI Models & Operations
Built-in AI models enrich data, such as sentiment analysis and PII redaction. Previously unstructured data can be searched or queried, and real-time streams can be monitored.

Categories & Use Cases

Media

Screenshot of Platform overview graphic

Anne-Marie Moore

COO (Chief Operating Officer) in Corporate at Media Sonar (11-50 employees employees)

Use Cases and Deployment Scope

The Datastreamer platform allowed us to easily set up the data pipelines that source and aggregate external social media data into our web intelligence platform. Great tool for teams that need to process massive amounts of text data but don’t want to dedicate personnel to maintain infrastructure or build in-house. Our team uses their AI models to classify data. We were able to get set up easily with their API interface, and are currently streaming social media data points into our core product.

Pros

API ease: Everything is done through APIS. We can readily adjust data parameters on our end to adjust to API changes.
Strong data breadth/coverage.
Strong organization of unstructured data from mulitple social media sources and tools to help us manipulate the data into useful format.

Cons

Need a visual UI to manage and build pipelines.
Need broader language coverage in text data analysis.
Improve support and user communication processes.

Most Important Features

Indexing unstructured data - helps with query building in our product.
NLP and AI - data aggregation and classification
Ability to transform/combine unstructured data from multiple sources into a common schema

Return on Investment

Positive: Saved months of development time to build infrastructure in-house
Positive: Saves hours per week supporting/maintaining any in-house substitute we would have developed

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