Data & Information Management

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.

DataOps

DataOps, the set of best practices, ameliorating coordination between data science and operations, has become a critical discipline for any IT organization that must survive and thrive in a world where real-time business intelligence is a competitive necessity.

What is DataOps?

DataOps is a collaborative data management practice focused on improving the communication, integration and automation of data flows between data managers and data consumers across any organization.

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?

E-Connect employs various stages to automate the design, deployment and management of data delivery with the appropriate levels of governance and metadata, refining the use and value of data in a dynamic environment.

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.

Loop 1

Sandbox

The data teams explore raw data for fast experimentation to have first set of unrefined analyses.

Loop 2

Staging

Data is appropriately cleaned, documented and initial models are refined through successive iterations enhancing quality till they are trustworthy enough to reach production.

Loop 3

Production

Refined analytical models are promoted to the production stage to be used by data consumers in their daily activities, where they are able to accelerate decision-making processes, generating long-term business value and ROI, leveraging acquired knowledge.

Data Governance

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.

Data Quality

Increase your data quality to leverage greater value from it. E-Connect has core competencies in aligning your organization’s data quality with business outcomes. We accomplish this by collecting data quality rules across your organization, reconciling any gaps, and continuously monitoring the quality of your data to ensure that it meets the requisite standard.

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.

Data Integration

Data integration across disparate data sources is necessary to support the solution. This requires consistent data definitions across an enterprise. The sheer number of data sources adds to the challenge of data integration. Many scenarios highlight data integration challenges:

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.

Data Security and Privacy

Data security and privacy is critical in today’s connected business environment. We have extensive experience. We have extensive experience working with senior management to understand data regulations and formulate data security policies across the enterprise. This includes identifying the most sensitive data and aligning it with appropriate compliances. We identify and define data-related controls to manage risk.

Meta-Data Management

We have the experience to fully develop effective metadata management strategies within organizations. Our approach begins with analysis of the current environment, applications and business needs surrounding metadata, followed by defining high-level business, technical and metadata solution requirements. We provide recommendations on approach, architecture, governance, risk assessment and other topics with a roadmap and high-level project plan. Leverage our experience as well as our proven project methodologies and templates.

Master Data Management

Data management in large organizations is extremely complex. Master data management addresses this challenge, leveraging your data for greater organizational value. We help you define and understand MDM and the extraordinary value you can reap from it. We provide an overview of various architecture types for MDM and help you determine and implement the services best-suited to your organizational needs.

Improve Decision-Making and Business Performance with E-Connect.

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