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Aug 12,2020 04:41:57AM
Why is Data Strategy so important?
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Building the Caliber for Enterprise-Wide Futuristic Data Systems

 

 

Data is more than just a buzzword; it has become the fuel for enterprise engines to ignite critical processes in the right perspective and direction. Organizations are looking to tap the most from the improvements in data storage capabilities across platforms and key vendors towards a build-up of coherent, flexible, innovative, and reliable information assets. It involves identifying and fixing inconsistencies arising out of legacy data storage and usage platforms – and seamlessly upgrading or replacing them with modern or ad-hoc data storage and retrieval systems. With need to manage complex resources and technology behind the data-centric needs of companies, thought leaders have identified the need for a Chief Data Officer, depending on the hierarchy and ‘command matrix’ of individual firms.

Modern data platforms and offerings are characterized by an all-inclusive portfolio that covers data privacy, architecture, governance, and overall storage – along with the costs associated in accordance with the premium or standard labels. The scope and boundaries of data-centered operations have become so broad, as market is bustling dedicated vendors who can offer custom infrastructure and tools to actually formulate and meet data management needs. In this scenario, enterprises are increasingly focusing on deriving value out of a multi-prone data strategy with a consolidated enterprise-wise schema of business data and entities.

Throughout its journey, NYGCI (Data Protection Services Company) has adopted a scientific yet holistic approach in evaluation and assessment of the needs of internal resources in terms of building a solid data systems competency. It was able to determine key vitals as well as pain points to set our goals vs. expectations for stable data-centric system landscape encompassing people, technology, processes, and organizational levels. This helped us work around and shape key parameters towards a world-class enterprise data strategy that would serve client needs and push our capabilities seamlessly.

• Transform in terms of scale as well as speed
• Eliminate sheer dependency with flexible data ecosystem
• Tackling data silos by way of merging and connecting
• Compliance with prevailing data governance norms
• Security and privacy of confidential business data

With evolving business needs, we understand that businesses must be looking at diverse yet seamless platforms, applications, and capabilities around data – that can perform cohesively with the least consumption of resources and within optimum levels. To make this a reality and carry this proposition to new-age transformation, we can offer an integrated ‘semantic’ layer. Data-driven initiative of ours has helped a number of lients to achieve growth and optimize costs on infrastructure planning. These customized offerings essentially perform and delivers value in the form of a unified and well-integrated cloud-based data platform.
Technology and business thought leaders have zeroed in on some critical parameters to build data strategy, which essentially revolves around five components with the letter S.

Stability: Reliable, persistent, and robust data solutions to ensure business diligence and continuity of processes.

Seamlessness: Clean data that is ‘free’ of residual values and garbage to produce intelligible and actionable insights across customer touch-points.

Security: Data architects can ably build systems that never compromise on critical business data and sensitive customer information, thereby adding immense trust.

Scale: Data systems that are stable enough to deliver business performance across the enterprise resources and can scale to fulfill expanded business demands.

Speed: We place emphasis on the diligence of data-driven platforms in view of critical processes that require efficient and instant processing of information in real-time.

We are consistently working on creating cutting-edge data systems based on modern architectures such as the Data Lake, for progressively helping us serve our client needs more efficiently. We have built data capabilities that support various cloud-based configurations offered by AWS, Azure and mainframe-hosted data storage systems, Big Data vendors, as well as open-source data technologies. NYGCI resource planning, skill development, team building, and constant understanding of the data ecosystem across various business domains has been a prioritized area.

NYGCI also provides DPaaS (Data Protection as a Service), Big Data Analytics (Analytics as a Service), & STaaS (Storage as a Service)