As more businesses adopt a data-driven approach, the Business Intelligence (BI) and analytics market is experiencing exponential growth. However, the current BI landscape presents a myriad of features, making it a challenging task to discern which ones are crucial for driving impactful business outcomes.

After thorough market research, analysis of customer interactions, and discussions with industry experts, we've compiled a comprehensive list of seven analytics trends set to shape the BI landscape in 2024. Recognizing and embracing these trends can unlock the full potential of your business data, paving the way to establish an insights-driven business model.

1) Data Pipeline and Preparation by Business Users

Data preparation was once a time-consuming task requiring IT intervention. However, self-service ETL is revolutionizing the data pipeline and preparation process through AI and automation. With a low-code/no-code approach, self-service ETL now offers lightweight, user-friendly capabilities as a native component of the BI stack.

Meeting the needs of pro-code users while enabling custom model deployment, the modern ETL layer also supports prebuilt data preparation models, dramatically accelerating time to insight. Explore some of these data preparation capabilities in the demo video below.

2) Unified Business Analytics

As businesses increasingly use applications for daily operations, the demand for end-to-end 360° business insights is growing. Unified business analytics seamlessly integrates data from various sources, setting up a common semantic model for joint analysis. This empowers users to gain a holistic understanding of overall business performance and assess the cross-functional impact of different teams and functions.

BI vendors are driving unified analytics by enabling seamless native data connectivity with a variety of business apps and data sources. This approach overcomes challenges associated with data silos and disparate datasets, fostering a more holistic approach to data integration. Furthermore, with an AI-infused analytics layer and domain-agnostic prebuilt reports, modern analytics platforms enable deeper domain-specific insights that can be derived seamlessly.

3) AI-infused BI

AI has become an integral component across the entire BI stack, encompassing data import and preparation, modeling, visual analysis, predictive analytics, insight generation, and beyond. Seamlessly integrated into these functionalities, AI streamlines and enhances analysis, providing both simplicity and depth.

Key trending AI-powered capabilities today include NLP-powered analytics assistants, enabling report creation through natural language, automated insights, and prescriptive analytics. These features empower users to delve deeper into reports, uncover hidden insights, and receive instant recommendations for decision-making. Additionally, AI plays a significant role in data science and machine learning (DSML) capabilities, further augmenting analytical capabilities and driving innovation in BI.

4) Generative AI in BI

Generative AI (GenAI) emerged as one of the most significant AI waves of 2023, profoundly transforming the BI landscape and leaving a lasting impact across all industries. GenAI has the potential to democratize analytics significantly, adding speed to BI adoption worldwide through simplified data interactions, automatic generation of models and metrics, identification and construction of comprehensive datasets, and beyond.

We also foresee the integration of domain-specific LLMs in BI platforms in the coming years, significantly enhancing the relevance and depth of insights. GenAI is expected to play a crucial role in bridging the divide between BI users and analytics platforms.

Stay tuned for the continuation of the trends...