Accelerate digital transformation with data analytics

Accelerate digital transformation with data analytics

In the current digital market, customers demand immediate, relevant, and tailored interactions with the organization they choose to do business with. It is no wonder then that data and analytics shared the top spot in the 2019 CIO Tech Poll study for the biggest expected budget increase over the year (47%) with alongside disaster recovery.

As Matt Feyling, Vice President, Analytics Practice at Trianz observes, "To meet the growing expectations of modern consumers, it is absolutely vital that organizations consider and understand how to effectively capture, use, and measure the impact of their data as part of their digital transformation."

How can your organization benefit from using data analytics?

• Modernize Strategy and Governance to avoid data swamp

Although organizations have deciphered how to build data lakes, they still struggle to monetize the data as quickly as they had hoped. It's because they are unprepared to answer questions on different and voluminous data assets. Make sure you modernize the strategy covering vision, goals and mission around Process, Technology/Tool and People.

• Build Intelligent and Empowered data lakes

Data explosion in data lakes would make it impossible for humans to completely explore and monetize data because data lakes do not deliver anything by themselves. Design and build data lakes with automated data crawlers and AI capabilities that continuously identify patterns and build the data web connecting layers across fragmented and distributed data assets. This creates a platform that enables greater and faster analytics validation and monetization.

• Enable Augmented Analytics

Combine BI and AI/ ML practices in your organization to enable the Augmented Analytics system. While you automate data collection and engineering with ML, allow human intelligence to think about different hypotheses and actionable insights. NLP will continue to be a growing trend in enabling Augmented Analytics in the industry in this sense.

• Embedded Analytics

Although enterprise data lakes focus on connecting dots, it is important to have siloed/embedded analytics. In fact, do not design and build any business workflow/function/microservice without embedded analytics focus. Every business or system event must be measurable for its efficiency/value in real-time and must be subjected to continuous improvements.

Business decision makers now have access to increasingly accurate and innovative means of collecting data and translating it into organization value to reap these benefits — not to mention improvements to customer experience, such as machine learning. Yet, in today's digital strategies, data as an asset remains a grossly under-utilized tool. Studies suggest that very few organizations are ready to deliver real-time, data-driven engagements; even fewer can ascertain their impact on the bottom line.

Making the leap

This disparity represents a strategic opportunity for organizations to get ahead of their competition as they focus on their digital transformation. Despite the increasing availability of tools, however, it isn't an easy opportunity to seize. The complexities involved leave many organizations struggling to move past their analog models and processes.

Thankfully, it is not a leap you have to take alone. Digital Transformation partners like Trianz can help you build your data and analytics strategies, and figure out how to efficiently develop and fully capitalize your information assets.

As you begin or continue your digital transformation initiatives, an effective use of data and analytics will help you make the transition with grace and agility.

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