Expert Tips For Making The Most Of Cloud-Based Data Analytics

Many companies rely on data-driven decision making for its capability to spot trends, improve processes, better serve customers and much more. Cloud-based data analytics can be a very powerful tool to help businesses gain valuable insight and information by leveraging the the actionable insights that companies use from the smart decisions provided. Below, expert members of Forbes Technology Council share their expert tips to help businesses make the most of cloud-based data analytics.

1. Leverage GenAI For Connected, Contextual Insights. “Enable generative artificial intelligence on your data analytics platform. Connect data, operations, people and decisions for dynamic visibility and continuous intelligence. This empowers your team to turn disruptions and uncertainty into opportunities with accurate predictions and real-time, connected, contextual insights. This leads to data-driven decision making that is customer-centric and profitable.” – Roshan Pinto, Tavant
2. Tap Into Enhanced Computing Power. “Businesses can leverage cloud-based data analytics to access enormous computing power without significant upfront costs, enabling them to train models on large datasets quickly. Once trained, these models can be applied to drive business value. Additionally, the cloud excels in real-time decision making, where speed is essential, such as tailoring unique solutions based on prospect data.” – Peter Bajwa, App-scoop Solutions Inc.
3. Easily Connect To Various Data Sources. “Cloud-based platforms enable companies to simplify the complexity of connecting to various data sources, empowering engineers to immediately leverage existing data to address corporate initiatives with minimal capital investment. For example, with insights from these platforms, engineers can power a range of use cases to drive sustainability progress, including analyzing environmental, sustainability and governance initiatives’ performance against goals.” – Dustin Johnson, Seeq
4. Combat Fraud. “Fraud losses total in the billions each year. Cloud-based fraud analytics enables specialists to focus on critical risks while machines handle lower-threat incidents autonomously. A good use case is merchant onboarding. Payment providers deploy cloud analytics to swiftly and accurately assess risk, capturing new merchant business without compromising due diligence.” – Rochelle Blease, G2 Risk Solutions
5. Monitor Customer Behaviors. “Conduct real-time data processing to improve decision making. Collect, process and analyze data in real time to get up-to-date insights on business operations. For example, an e-commerce business can use cloud-based analytics to monitor customer behavior on its website in real time to detect purchasing patterns.” – Venkat Viswanathan, LatentView Analytics
6. Strengthen Identity Governance. “In terms of identity governance, businesses can leverage cloud-based data analytics to continuously monitor access patterns and user behavior. This enables real-time anomaly detection and can flag potential risks, allowing for more accurate access controls and policy adjustments. This strengthens security and compliance while ensuring the right people have the right access at the right time.” – John Milburn, Clear Skye
7. Establish An Enterprise Data Dictionary. “Analytics and insights are only as good as the underlying data being used. Make sure your data is sound, well-defined, not missing key components and secure. Ideally, you want to have an enterprise data dictionary or glossary so the entities are defined reasonably consistently across systems and the data lake.” – Pankaj Chawla, 3Pillar Global
8. Create Dynamic Dashboards. “Businesses can harness cloud-based data analytics by integrating real-time data streams from various sources to create dynamic dashboards. These dashboards provide up-to-date insights, enabling data-driven decision making and allowing businesses to quickly respond to market trends and operational challenges. The cloud’s scalability and accessibility make it ideal for this approach.” – Sivanagaraju Gadiparthi, ADP
9. Standardize Product And Supply Chain Data. “Cloud-based data analytics can be used to standardize quality product and supply chain data across departments, enabling businesses to make better-informed decisions at an accelerated pace. More specifically, these offerings provide instant impact assessments and real-time data updates that can generate insights to help companies optimize product costs, measure environmental impact and ensure compliance.” – Neil D’Souza, Makersite
10. Integrate AI-Driven Predictive Models. “Businesses can maximize cloud-based analytics by integrating AI-driven predictive models. By analyzing historical data and trends, these models forecast future scenarios, enabling proactive decision making. This strategic foresight empowers companies to anticipate market changes, optimize resource allocation and enhance competitiveness, transforming data into a predictive tool for sustained growth.” – Rohit Anabheri, Sakesh Solutions LLC
11. Include Data From Third-Party Providers. “By integrating aggregated data from third-party providers, most businesses can significantly enhance cloud-based data analytics. Modern cloud platforms facilitate easy connections to these sources, enriching company data and providing deeper insights for crucial decision making. This enriched data helps leaders make more informed and effective business decisions.” – Rodion Telpizov, SmartJobBoard
12. Explore Real-Time, Broad-Ranging Scenarios. “Modeling and predictive analytics allow decision makers to efficiently explore a larger scope of scenarios in real time without being restricted by limited resources or outdated data. For example, drug developers or healthcare practitioners can individualize drug therapy to a patient based on their recent lab results via simulation of potential dosing strategies or drug treatment combinations.” – Patrick Smith, Certara
13. Analyze Historical Data And Market Trends. “Businesses can leverage cloud-based predictive analytics to forecast demand by analyzing historical data and market trends. Manufacturers can optimize production and better manage supply chains, while retailers can adjust stock levels and plan promotions. This proactive approach minimizes waste, improves customer satisfaction and enhances profitability by anticipating future needs.” – Sumit Bhatnagar
14. Adopt A Data As A Product Approach. “To maximize cloud-based data analytics, businesses should adopt a data as a product (or DaaP) approach. By treating data like a product, including having dedicated teams for development and life cycle management, companies ensure high-quality, accessible data. This method drives actionable insights, enhances agility and scales efficiently, embedding data deeply into strategic decision making.” – Suri Nuthalapati, Cloudera
15. Anticipate And Prevent Downtime. “Implement cloud-based predictive analytics to anticipate and prevent system failures or downtime. By monitoring software performance metrics, companies can schedule proactive maintenance and reduce unexpected outages.” – Vamsi Krishna Dhakshinadhi, GrabAgile Inc.
16. Dig Into The Details Of Transaction Costs. “My favorite insight that’s made easier in the cloud is realized by leveraging metadata on resource consumption and spending and then tying it to the cost of a transaction (a useful metric for transaction-driven businesses). Serverless functions and the like make it simpler to first understand per-transaction costs and then optimize.” – Kim Bozzella, Protiviti
17. Establish A Data Lake To Monitor And Respond To Live Metrics. “Most software as a service companies and other cloud tools offer data downloads. Having a data lake with integrated cloud-based analytics and real-time data feeds allows a business to monitor and respond to live operational metrics. This capability supports agile decision making and rapid adjustments to strategies based on real-time performance indicators.” – Hadi Tabani, Liquid Technologies
18. Leverage Quantum Computing To Tackle Complex Problems. “Businesses can use quantum computing integrated with cloud-based analytics to solve complex optimization problems that were previously unsolvable. This allows companies to uncover hidden patterns in massive datasets and make real-time, highly accurate predictions. Using quantum-enhanced insights can revolutionize decision making, providing a competitive edge in rapidly changing markets.” – Dr. Reji Thomas, TOL Biotech
19. Deploy Human-Centric Predictive Analytics. “Businesses can efficiently use cloud-based data analytics by deploying human-centric predictive analytics. By integrating cloud-based data with behavioral psychology, companies can discover the “why” behind behaviors using predictive analytics models. This human-centric approach empowers businesses to design personalized customer experiences and products, driving both customer engagement and loyalty.” – Jabin Geevarghese George, Tata Consultancy Services
20. Cultivate A Data-Driven Culture. “Implement monthly events where all employees, regardless of role, use simplified cloud analytics tools to explore company data. This democratizes data insights, uncovers unexpected patterns and cultivates a data-driven culture across the organization, leading to more diverse and innovative decision-making perspectives.” – Echul Shin, Eternis

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