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Cloud Analytics: Utilizing Composable to turn your organization into a Data-Driven Company

Andy Vidan

Major transformations are shaping the global economy, and it is now clear that organizations with the resources and know-how to leverage the large volume of both internal and external data being generated today have the competitive advantage. However, gone are the days when data analytics is available only to the largest of organizations, with dedicated budget, resources, and business analysts.

Cloud Analytics, enabled by platforms like Composable, are now available to all organizations, regardless of size, that embrace new shifts reshaping computing and business intelligence. These include:

  • The role of the “business analyst” now applies to all users in the organization. All tasks across the business can benefit from data-driven decision making, and all business users can and should have access to user-friendly, self-service tools to enable them to think and act as a business analyst.
  • Large capital investments are no longer needed for computing infrastructure. Organizations can and should leverage the cloud as much as possible.
  • Dedicated internal software development teams building internal tools are no longer required. Technology is changing too quickly, and new software tools are available constantly, for a team to spend time stitching together third-party tools and services in order to leverage their data. Again, organizations can leverage self-service tools that are constantly updated to leverage the newest technologies and provide the needed capability at scale and at an effective cost.

Composable has allowed small, medium and large businesses to transform into data-driven technology companies. The Composable platform was developed with the above factors in mind: business users, regardless of technical ability, want to have access to data and state-of the-art analytical techniques; the cloud must be leveraged; and integration with new software tools should be straightforward.

The Composable platform was architected as a native cloud app to automate and simplify big data analytics, and in turn, allow organizations to improve their competitive advantage by becoming digital masters. It offers users powerful features improving the analytical workflow, with integrated capability for data ingestion, analytics and visualization.

Composable’s open data approach supports ingestion of data from traditional and non-traditional sources. These include flat files, such as a CSV or XLSX, and RDBMS like MySQL, PostgreSQL and SQL Server. In addition, non-traditional sources are easily integrated, such as NoSQL databases, triple stores and new high performance databases. Various data formats are also supported, including image, video and audio files.

Advanced analytics is as easy as plug-and-play in Composable, as the platform utilizes a flow-based programming methodology where an analytical workflow is represented as a dataflow. A dataflow is a directed graph with modules at the nodes. Modules have inputs, perform an execution step, and then produce outputs. In addition to ingestion, processing, cleansing and other functions, modules can perform advanced analytical functions, to facilitate the fusion and exploitation of data. In this way, dataflows can span the entire data analytics stack, performing the extraction, transformation, loading, querying, visualization, and dissemination functions. Composable is, in this way, a natural platform in the emerging area of IoT (Internet of Things) Analytics, where each module in the dataflow can correspond to a device or service that is streaming data.

Cloud Analytics is the competitive advantage an organization needs to transform into a data-driven technology company. The Composable platform is the leading turn-key solution that can enable an organization to embrace this transformation.

Andy Vidan

Andy has diverse and extensive experience spanning data sciences, information technology and applied physics, with a passion for developing and scaling disruptive technology platforms. At MIT Lincoln Laboratory, Andy served as a key technical contributor to a broad range of homeland security and defense research programs, and was the architect for the Laboratory’s Distributed Disaster Response program, developing advanced information systems for large-scale crisis response and management. Andy has a PhD from Harvard University and a BS from Cornell University.

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