By Olivia Cahoon
Analysts spend a considerable amount of time preparing data and organizing it into impactful analyses. With the need for a faster solution, companies create self-service analytics tools designed for business users.
Established in 1985, Datawatch is headquartered in Bedford, MA, with offices in New York, London, Frankfurt, Stockholm, Singapore, and Manila. The company also has partners and customers in more than 100 countries worldwide. A public company, it reported a total revenue of $30.46 million for the 2016 fiscal year.
Datawatch enables ordinary users to deliver extraordinary results using all of their data. “We unlock data from the widest variety of sources and prepare it for use with visualization tools or other business processes,” says Frank Moreno, product marketing VP, Datawatch.
The company allows organizations to visualize streaming data for demanding business environments in a period when real-time visibility to rapidly changing data is critical.
At the arrival of self-service analytics tools designed for business users, Datawatch recognized the need for a complementary self-service data preparation solution and created Datawatch Monarch.
Monarch is an application that runs on a Windows desktop and automatically extracts dropped files or webpages into analytics-ready rows and columns. The application uses simple drag-and-drop features for effortless data management and is available as a desktop application for $1,595 per year. The application has evolved over the 20 years it has been on the market.
Monarch uses Windows 7 SP1, 4 GB RAM, and 600 MB disk and is accessible from all major databases. Because business agility is best achieved when business users and data analysts can interact directly with all their data, Monarch is compatible with CSV, XML, JSON, OData, HTML, Excel, PDF, Web APIs, relational databases, and NoSQL sources. “IT becomes the hero when they choose solutions that business users love and can be deployed at any scale required,” suggests Moreno.
Datawatch created Monarch after it observed how data is controlled by IT and business intelligence (BI) gatekeepers. “Teams are limited to sharing what little data they have via personal Excel spreadsheets, increasing compliance concerns and reducing the trust in their analysis,” explains Moreno. IT and BI also struggle to balance the ongoing need for standard reporting, maintaining data governance and regulatory compliance, and improving responses and delivery times. Monarch acquires and prepares data from any source, eliminating redundant work across different departments, share techniques, and curate data with their peers.
Building at the success of Monarch, Datawatch’s next step in the evolution of data accessibility and self-service analytics is data socialization. Moreno shares that data socialization is reshaping the way organizations think about, and employees interact with, their business data. Data socialization combines self-service visual data preparation, data discover and cataloguing, and automation and governance features with a data management platform.
For the past 12 months, Datawatch has developed Datawatch Monarch Swarm to extend data access and incorporate data socialization. Good candidates for Monarch Swarm include healthcare, financial services, federal government, state and local government, retail, manufacturing, and telecommunications industries.
Moreno says that Datawatch began development on Monarch Swarm as a direct result of the rapid innovation of self-service data preparation over the past year. Some of the recent milestones include access to dark data locked in PDF documents, point-and-click access to critical business data sources, drag-and-drop access to Web and third party data, automated and predefined preparation functions, direct exports or analytics-ready data, and built-in automation and governance functionality for security and compliance.
Datawatch Monarch Swarm includes a range of features like cloud-based data preparation for preparing self-service data that provides access to everyone, everywhere. It will also allow employees to easily find and use data that has been made accessible to them and creates a social network of certified curated and raw data sets for everyone. Other features include crowdsourcing, intuitive search, machine learning, data quality and governance, and automated operations.
“Datawatch Monarch Swarm extends data access and enables self-service analytics to all levels of the enterprise including individuals, workgroups, IT, and BI workers as well as business analysts and information workers,” says Moreno.
Data socialization enables business users, analysts, and data scientists to search, share, and reuse managed data for enterprise collaboration with the intent to learn from each other, be connected, and stay productive. Datawatch extends its Monarch solution with its successful Swarm, bringing industries data socialization that aids ordinary business users to achieve exceptional results with any data. SW
Nov2016, Software Magazine