THANK YOU FOR SUBSCRIBING
Investing in BI and analytics is necessary for businesses to analyse the infinite data generated. Therefore, it is essential to understand the latest developments for a future-ready industry.
FREMONT, CA: Some businesses are still recovering from the impact of the pandemic, while others are attempting to meet and outperform expectations. Regardless of their current phase, business intelligence (BI) plays a vital role as the key technology enabler that allows companies to navigate unforeseen change and ensure business continuity steadily. Therefore, BI will introduce new trends to help organisations grow their business analytics program.
The digital revolution has found a stable place in the contemporary business environment. Companies receive improved access to data to maintain collaboration and productivity among distributed workforces by shifting data to the cloud. Businesses are equipping themselves with the power of cloud analytics to gather actionable, timely information from that data. Analytics in today's landscape can be flexibly deployed on public, private, hybrid, multi-microservices, or community clouds, depending on the budget, security, compliance, hardware, and other factors. This will further spur the adoption of cloud analytics.
Unified Data Management and Analytics
The inventive unification of the BI stack has transformed the visualisation implications into modern BI and analytics solutions. Many additions and integrations are occurring in the data preparation layer. This made it possible to connect, explore, change, and enhance data for analysis. The supplementations include data management, consolidation, preparation, and insights. However, a new approach, AI and ML, have recently become the most popular in joining the BI full-stack, which redefines self-service analytics and enables the intelligence programme to be widely accessible within organisations. Incorporating automation capabilities into this solution will result in a robust BI programme that runs on auto-pilot and empowers teams to make data-driven decisions rapidly.
The wider adoption of technologies and applications leads to various analytics consumption points. One example is the evolution of natural language query (NLQ) capabilities into immersive conversations. This has led to BI implanting among business users and providing in-context analytics, becoming a critical function for BI suppliers. Therefore, analytics platforms embed AI and ML capabilities across multiple points in business workflows for contextual insight discovery.
In addition, decision intelligence gaining broader momentum leverages the framework for decision-making best practices, which supports the application of ML at scale. They also act as enablers that complement decisions made by humans. Automated insights are one such facilitator. It strengthens visualisations with information in the form of narratives, giving more power to effective decisions.
360° Business Analytics
BI platforms are becoming more data agnostic and expanding their stable business app integrations by embracing more business apps across companies. This is producing more opportunities for data integrators. Native app integrations and developments in prebuilt, domain-specific data models enable businesses to receive insights faster without the need to build reports and dashboards. Such models are also capable of being trained to handle specific business requirements. Moreover, auto-modelling and blending capabilities are making it easier and faster to analyse complex datasets. This contributes to real-time, cross-functional analytics that provides 360° of business insights.