Data & Information Management
Augment decision-making with data-driven visual analytics and intelligence
Enterprise data & information management depends on an integrated data architecture that facilitates the retrieval, analysis and manipulation of data across all functions and business units, as well as several applications. The challenge in today’s environment is that this information is scattered across several applications and diversified platforms. An integrated data architecture, necessitates implementation of sophisticated processes and methodologies in compliance with changing regulations. To leverage maximum value from data, organizations need an efficient process and foundation for handling the data architecture and creating an efficient way to securely manage data across the enterprise.
At E-Connect, our data management services provide innovative enterprise solutions, customizable to fit the information needs of any organization, helping drive better decision-making and improve business performance. We offer a complete spectrum of enterprise data & information management services.
What is DataOps?
E-Connect’s DataOps Service is employed to address the following challenges :
- Unsynchronized departments
On account of discrepancy in data and analytics goals and culture, it is essential to employ consistency among different stakeholders operating in silos.
- Process inefficiency
Time and budget-consuming, homegrown big data solutions end up into impoverished technologies leading to high-risk.
- Technological impairment
Integration and sustenance of ever-evolving Big Data and AI landscape is cumbersome and often overseen as high-risk investments.
How E-Connect implement DataOps?
The succession of stages, referred to as data pipeline, where data flows, beginning with extraction from myriad of data sources till visualization for business consumption. Leveraging CI/CD practices, it orchestrates and automates the pipeline to ensure optimum production.
This process is illustrated by the succession of three loops, in which data models get promoted between environments, as new data is added in the pipeline.
Concerns Pre- & Post-Process Implementation
Pre-processes pertain to the highest levels of business. Decisions are made regarding the sanctioning of data. This involves creation of policies and decisions around permission to use data and how to use data.
Post-process involves daily strategies that support the ongoing formulation of policies for data.
Better Data Governance = Higher Confidence in Accumulated Data
Strong policies for data governance must include data security and data privacy concerns. This ensures higher data quality across your entire organization.
Better Data Quality = Better Data Integration
Strong levels of data integration are essential for the solution to succeed. We drive continuous improvement of integration by leveraging meta-data management along with master data management.
- Mergers and acquisitions
- New development systems
- New application systems that require integration
We have extensive experience in this area and have helped several customers create initiatives including metadata management and master data management, aligning with the Service Oriented Architecture (SOA) and standardizing platforms with consistent data definitions throughout the organization.