Creating evergreen value with AI, data, and analytics

You know that feeling when spices come together to create the perfect blend, when choir voices harmonize, or when the last piece of a jigsaw puzzle slips into place?

Satisfaction. Stars are aligned.

Similarly, when effective data management practices are implemented, data becomes a strategic asset that businesses can rely on for insights and competitive edge. If data is made accessible, trusted, and accurate, companies can confidently utilize it to improve business operations, achieve newfound efficiencies, and identify and pursue new revenue streams. The stars start to align for evergreen growth and value.

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All organizations face data challenges

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Managing data volume and enabling accessibility
Let’s face it. There’s so much data from so many sources that it can be overwhelming to access, track, and store. Clearer strategies for how data is processed and where it resides (either at the source or in data platforms) often need to be better designed and implemented.

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Ensuring the quality of data
Unclear, convoluted, or missing governance policies across organizations can often create ambiguity regarding ownership and accountability when it comes to ensuring the quality of data. Data duplication, missing data, and other inaccuracies can occur, and no one knows which is correct or the most up to date. A solid data strategy is lacking.

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Meeting the demand for analytics
Every department in the organization would like better insights to make better decisions. AI and analytics, from basic reporting to new machine learning models, require easily accessible, clean data so an organization can strengthen its decisions, operations, and engagement. Organizations can’t start from scratch every time.

There are sound AI and data operations solutions.

If an organization focuses on available and accessible data, enables scalable infrastructure, governs data with confidence focused on a set of wider objectives, and automates processes for efficiency, then data will deliver insights—and business value with it—elevating data into a strategic business asset for the company. The stars for AI, data, and analytics begin to align.

Where should companies start?

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Take a comprehensive DataOps approach

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DataOps is the comprehensive suite of activities and capabilities that enables data to be stored, managed, maintained, and monitored so it is accessible, trusted, and accurate. Four key principles drive a strong DataOps program to successfully enable AI and analytics.

First, the data must be available and accessible, seamlessly integrated across platforms, and ready to serve up analytics and insights (DataCOREOps).

Next, it must be on reliable, scalable, and efficient infrastructure (DataINFRAOps).

Third, it must meet quality expectations—the data must be clean, trusted, and accurate with clear governance policies in place (DataGOVOps).

Finally, the process must be automated to reduce errors and save time (DataSMARTOps).

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Put accurate, scalable, intelligent data to work today.

With a reliable DataOps program in place, AI and analytics generate trusted insights. Organizations can increase speed to decisions and create analytics that lead to evergreen business value.

Once data is a strategic asset, there’s no limit to what AI, machine learning, and analytics can yield for your organization. A DataOps program that prioritizes data readiness, scalable and resilient infrastructure, and transparent and flexible governance - and leverages automation - is the gateway for success. When stars align for AI, data, and analytics... that’s satisfaction.

Download the REPORT

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When stars align for AI, data, and analytics... that’s satisfaction.

Get in touch

Jim Rowan


AI and Data Operations Offering Leader

Prakul Sharma

Managing Director

Data Operations Practice Leader

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