The aim of developing a bridge between data sources and business user processes is improving business intelligence (BI) and decision-making. Hence, trends in data analytics and BI are largely intertwined.
A business’s success relies on models, methods and data-driven decision-making. But a surfeit of marginally usable data can lead to errors and inefficiencies. Modern trends in data analytics and BI generally surround the two criteria that matter most: data quality and application. Monitoring and understanding these trends helps businesses find a competitive advantage.
Below are some trends that apply to the discipline of data analytics as a whole.
Data Storytelling
Data storytelling involves distilling large amounts of data into terms and formats that laypersons can understand. As the term implies, this means using data to tell an understandable story that can inform BI decision-making and management at all levels.
Data Discovery and Visualization
Data discovery allows end users to construct their own understandable story from data analysis. According to BARC, data discovery “is the business user-driven and iterative process of discovering patterns and outliers in data.” Data discovery makes advanced analytics processes more user-friendly. The result is simplified visualizations of data.
Self-Service Analytics and Business Intelligence
Self-service analytics and BI refer to business users having more independence in their interaction with BI tools. These BI tools may allow for basic data discovery and visualization for users with more casual needs or offer more in-depth functionality for advanced users and full-fledged business analysts.
Embedded BI
Embedded BI is an example of self-service BI, integrating business intelligence tools into existing business applications. This may come in various forms, including BI dashboards, reports or predictive analytical models embedded into existing applications.
Real-Time Analytics
Real-time analytics allows data discovery and visualization through mediums such as embedded BI tools to represent constantly updated data and advanced analysis. This ensures self-service BI provides business users with accurate, up-to-date and ongoing analysis to inform decision-making and strategy iteration.
Data Governance
Data governance encompasses the processes and policies surrounding an organization’s use and management of data. It has become an important consideration for businesses facing a glut of information and the need for compliance in various regulatory environments.
Data-Driven Culture
According to BARC, “the concept of a data-driven culture treats data as the main resource for leveraging insights in every department of the organization.” This represents a shift from a traditional reliance on gut instinct and perception. It suggests that companies must go beyond data literacy for a few, with all employees becoming competent in data-driven decision-making.
Data Quality Management
Data quality management (DQM) encompasses data collection and analysis as well as the integration of analytic services and BI tools. It seeks to leverage information as a business asset and competitive advantage.
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Sources:
BI-Survey: Top Business Intelligence Trends 2021
BI-Survey: Creating a Data-Driven Culture
Datapine: Top 10 Analytics and Business Intelligence Trends for 2021
Dataversity: What is Data Governance?
Forbes: Data Storytelling: The Essential Data Science Skill Everyone Needs
Logi Analytics: Embedded Business Intelligence
