Building Verticals using DeepHouse Self-Service Platform

Almost all the industries rely heavily on data for management and growth of their business. Data driven models are no longer a luxury of large organizations and is necessary for small businesses to take off. A large part of Data Analytics depends on Ingestion and pre-processing of data. From simple reporting requirements in a website to large-scale advanced Machine Learning and AI insights require pre-processing steps consisting of Initial Data Analysis, Data Modeling, Database decisions, and Automation. The above processes that form part of DataOps are not standardized. Different organizations utilize variations of best-practices to Extract, Transform and Load in to databases. A lot of information can go unnoticed due to change in data formats and can end up with vast amounts of unusable data in large databases or data-warehouses thus incurring losses. iDap helps the DataOps pipeline step-by-step from Initial Exploration to Continuous Intelligence. Almost all data analytics that are domain specific will require the above processes. iDap will reduce time-to-market of your product rollout by virtue of its Customizable DataOps Management as a Service. With data-driven world being the norm, the platform will aid in pursuit of bringing your concept of value added service based on domain specialization to an actual deliverable in a fraction of the time needed if it has to be started from scratch. 

The main features of iDap are

Simple Data Ingestion from files that can be uploaded, pushed or streamed.

Configurable Readers based on incoming data format

Configurable output databases with recommendation based on the observed schema

Configurable data processing with an ability to integrate existing user’s API. For instance, metadata extraction, text extraction, data decryption.

Simplified data modeling using automated schema identification. 

Easy and intuitive Data Modeling. 

Ease of Integration from different sources including from popular vendors

Configurable Standard Machine Learning algorithms provides outcomes based on currently ingested data.

Explore data and create quick insights that can enable iterative process of tweaking the data model.

Advanced user management enables secure data sharing at schema, model, or metadata level based on user role and permission.

Allows automation of data masking and data compliance clauses. 

Cost-effective solution for small to Large organizations.