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Precision Technology: Discovering New Frontiers of Data/Analytics

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Adaptive AI, edge analytics, and ecosystem strategies are helping companies compete with new-age business models.

2022 Data and Analysis: Key Trends

Technologies like artificial intelligence and machine learning were in their infancy a decade ago, but they have come a long way and are now as common as the cloud in enterprises in 2020 and beyond. If data is the new oil of the information age, analytical technology is the new oil plant.McKinsey’s prediction AI will become commonplace in enterprises by 2025 The competitive heat these technologies bring to the business environment is nothing short of devastating. Here’s how the field of data and analytics (D&A) is evolving today.

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  1. adaptive artificial intelligence: By enabling AI models to be continuously retrained by learning from new data and user interactions, enterprises can operate more models. AI engineering practices can help companies build this flexibility into their AI models.
  2. D&A Ecosystem Strategy: With the birth of data marketplaces and business-neutral exchanges, organizations participating in non-competitive data-sharing ecosystems can derive greater value from their own data sets.
  3. Context-driven data fabric: Metadata – In other words, enterprise data context is becoming the most sought-after commodity in the process of securing, democratizing, and operationalizing data. A metadata-driven data fabric helps organizations do just that by minimizing data management overhead.
  4. Connected data governance: In a distributed global enterprise, connecting multiple D&A governance efforts is key to minimizing redundancies and reducing AI risk. Connected data governance, enabled by digital platforms, can improve trust among business and technology stakeholders.
  5. Edge-powered analytics: As response latency increases for both consumer and employee experiences, empowering AI decision-making at the edge can deliver faster experiences. This will be enabled by an increase in edge services from cloud providers in the market and connectivity technologies such as 5G and Wifi 6.
  6. Flexible data store: Innovative data technologies like graph databases and NoSQL are enabling data engineers to reduce data preprocessing time. This accelerates enterprise data discovery and development of new AI and ML capabilities.

So how are these trends playing out in the real world of business?

Cross-industry perspective

From improving the employee experience to delivering a differentiated customer experience, D&A is now at the forefront of nearly every disruptive business strategy across sectors. Amplified by rising consumer expectations for digital experiences across all industries, D&A technology is helping businesses keep up with trendsetters. Here’s a snapshot of this dynamic from several industries.

retail

daily necessities

Telecom

manufacturing industry

oil gas

Enabling Business Technology Transformation with D&A

The lack of synergy between business data goals and technology roadmaps is a major cause of today’s slow digital transformation and low ROI. As a result, defining common data milestones is critical to unlocking the full potential of today’s D&A strategies. The first step in this effort is to accelerate data maturity within the organization. This includes the familiar steps of keeping dark data out of your enterprise and documenting policies that protect data storage and use in accordance with compliance and governance requirements. Additionally, identifying the data assets that give an enterprise a competitive edge must first be identified and operationalized in the right use cases. Building a data platform with a metadata layer defines the final stage of data maturity.

A well-orchestrated data and analytics-driven transformation should prioritize the development of use cases that generate rapid ROI along such data maturity roadmaps. Modern data analytics trends such as adaptive AI systems, edge analytics, and ecosystem strategies rely on modular architectures made up of multiple microservices. This enables organizations to improve key components of their use cases by integrating new technologies without rebuilding from scratch. Finally, keep in mind that your platform strategy will be critical in coordinating your D&A transformation strategy at scale. So what is it worth?

Strengthen new-age business model with D&A strategy

A D&A strategy has the potential to create new revenue streams for your business. For example, a large engineering organization can offer AI-powered maintenance his triggers to customers as a subscription service, and even turn her one-time purchases into lifelong customer relationships. Other ways his aforementioned D&A trends are unlocking new business models include monetizing data by sharing it across the ecosystem, directing additional revenue by improving user experience at the edge, and AI through connected governance. Includes risk mitigation. Combined with disruptive technologies such as IoT, 5G and edge computing, the innovation potential is endless.

Preface to the future

of data technology cost savings Bullish forecast for corporate spending on AI (Expected to reach $120 billion by 2025 in the US alone) shows the strategic value of D&A in the enterprise today and in the future. While these technologies will increase competition across industries, businesses should view this as an opportunity to lead the market. Moreover, the technology landscape is favorable to business. The cloud provider is rolling out new innovative data and intelligence services, edge computing solutions and his 5G services for enterprises. Technology (especially data) talent is in short supply, but leveraging collaboration with technology leaders will be his decade-long strategic play to drive business success with effective D&A strategies. .


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