The imperative to infuse digital technology into your organization is not new, but it’s more essential than ever that organizations embrace digital transformation and business continuity to improve processes. I have recently written about the need for digital innovation in business continuity, outlining the steps every organization needs to take. These steps involve a close examination of the digital technology they can apply effectively for business continuity during a pandemic, natural disaster, cyber event or geopolitical situation.
Effectively managing data privacy and security is a high-stakes matter. When an organization doesn’t get it right, it often becomes front-page news and occasionally becomes a subject of litigation. Yet organizations face an equally challenging imperative to ensure that business users have easy access to the data they need. Depending on how they are implemented, data governance policies can inhibit access to data, making it harder to find and utilize the data assets of an organization.
At Ventana Research we’re familiar with the need for digital transformation as we have been researching and providing education on this topic for almost two decades. And recent global challenges make even clearer the sea change at hand: digital innovation is essential for not only success, but survival. Business continuity during a pandemic, natural disaster, cyber event or geopolitical situation requires business and risk mitigation processes, but unfortunately very few organizations had been doing so. We are seeing how quickly organizations are going into survival mode, in how they operate and communicate to meet the expectations of the workforce, customers, stakeholders and potentially shareholders.
Artificial intelligence (AI) and machine learning (ML) are all the rage right now. Our Machine Learning Dynamic Insights research shows that organizations are using these techniques to achieve a competitive advantage and improve both customer experiences and their bottom line. One type of analysis an organization can perform using AI and ML is predictive analytics. Organizations also need to plan their operations to predict the amount of cash they will need, inventory levels and staffing requirements. Unfortunately, while planning begins with predictions, organizations can’t plan with AI and ML. Let me explain what I mean.
I was recently asked to identify key modern data architecture trends. Data architectures have changed significantly to accommodate larger volumes of data as well as new types of data such as streaming and unstructured data. Here are some of the trends I see continuing to impact data architectures.