Data is the heart of digital transformation and the digital+ economy. Data modernization moves data from siloed legacy systems to the digital world to help organizations optimize their use of data as a strategic asset. For a successful data modernization journey, the following are some important things you need to know: 

#1. Data Strategy 

A data strategy lays out your plan to improve how your business acquires, stores, manages, uses, and shares data. The creation of a strategy, according to McKinsey, ranks as the top reason for companies’ success in data and analytics. Your data strategy should include your vision, business objectives, use cases, goals, and ways to measure success. 

#2. Data Architecture and Technologies 

To improve access to information that empowers “next best action” decisions, you will need to transfer your data from outdated or siloed legacy databases in your on-premises data center to a modern cloud data platform. Gartner says that more than 85% of organizations will embrace a cloud-first principle by 2025 and will not be able to fully execute their digital strategies without the use of cloud-native architectures and technologies. For successful data modernization, your cloud data platform must be a cloud-native solution in order to provide the scalability, elasticity, resiliency, automation, and accessibility needed to accelerate cycles of innovation and support real-time data-driven decisions.  

#3. Data Analytics 

Another important part of data modernization is data analytics. Traditional business tools aren’t enough to support modern data needs. Advanced analytics such as predictive modeling, statistical methods, and machine learning are needed to forecast trends and predict events. Further, embedding analytics directly within applications and tools helps users better understand and use data since it’s in the context of their work.    

#4. Data Quality 

Quality matters a lot in data modernization because users who rely on data to help them make important business decisions need to know that they can trust its integrity. Data should be accurate, complete, consistent, reliable, and up-to-date. A collaborative approach to data quality across the organization increases knowledge sharing and transparency regarding how data is stored and used.   

#5. Data Security 

Strong data security is the foundation for protecting modern cloud data platforms. It includes safeguards and countermeasures to prevent, detect, counteract, or minimize security risks. In addition to security controls to keep your data safe, including user authentication, access control, role separation, and encryption, you’ll need to protect cloud services using isolation, a single tenant architecture, a key management service, federated identity/single sign-on, and end-to-end data encryption.  

#6. Data Governance 

Data governance determines the appropriate storage, use, handling, and availability of data. As your data modernization initiative democratizes data, you’ll need to protect privacy, comply with regulations, and ensure ethical use. This requires fine-grained techniques to prevent inappropriate access to personally identifiable information (PII), sensitive personal information, and commercially sensitive data, while still allowing visibility to data attributes a worker needs. 

Make Modernization Easier 

 Your modernization journey depends on a cloud data platform that eliminates internal data silos and supports cloud-native technologies. You’ll also need to choose the right data analytics tools, ensure that your data is trustworthy and implement solid data and cloud security and data governance. The Avalanche Cloud Data Platform can help make your digital transformation easier with proven data integration, data management, and data analytics services. Learn more about how the Avalanche Cloud Data platform accelerates data modernization so you can deliver today while building your digital future.  

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