In the current global, business environment, maximizing performance requires utilizing data analytics to achieve and maintain competitive advantages. Using data analytics to outperform markets begins with data collection.
Data Collection. Companies can utilize all relevant data that is available. This data can be collected internally within the company and externally from sources like surveys. Data can also be (1) structured in tables, (2) semi-structured in audio, video, and surveys, and (3) unstructured social media and documents.
Data Exploration. After collecting data, organizations can explore the data that has been collected. Data exploration helps companies find latent patterns, trends, and relationships in the data by using descriptive statistics and data visualization tools. Data exploration provides initial insights and understandings of the data.
Data Modeling. Next, organizations utilize data modeling to explain the types of data that exist, to explain the relationships of the data to other data, and to explain how the data should be organized and managed for optimal use by organizations. In summary, data modeling lays the foundation for deeper comprehension and optimized use of data.
Insight Generation. Insights generation analyzes complex data to reveal hidden patterns and unknown trends in data to provide businesses with a better understanding of its operations, customers, and market dynamics. In turn, insights generation fortifies decision-making, strengthens strategies, and improves outcomes and competitive advantages.
Communications. With the newfound knowledge gained from the insightful findings of the analysis, it is imperative to share the valuable information to appropriate stakeholders. Clear visualizations, such as graphs and dashboards, along with concise reports, are effective ways to communicate the results of the analysis. These visualizations and reports enabling stakeholders to quickly grasp the results and to make more informed and data-driven decisions.
In summary, data analytics uncovers hidden trends and relationships in data, facilitates the creation of predictive models, and provides robust frameworks for data-driven decision making.