What is Data Analytics?
Implementing a business intelligence solution involves using data to more effectively achieve mission objectives. Thus, it is a component of business intelligence, offering a comprehensive view into your processes. Data Analytics is the process of sorting, associating, and examining datasets to support decision-making, and extract valuable insights. Data analysis techniques can include specialized software, and even machine learning to sift through data and provide conclusions. Understanding your data can make your business more efficient, increase sales, brainstorm new products or services, retain customers, and more. Types of data that are commonly analyzed can include product sales, seasonal changes, profit margins, customer habits, or employee productivity. Comparing these data points, and organizing them into datasets to reach conclusions is the process of data analytics.
Data & Analytics Assessment and Roadmap
The data and analytics assessment identifies the current data analysis activities occurring in your organization, and compares it to best practices being deployed in your industry. Based on these insights, a roadmap is created to better collect and leverage analytics, along with prioritizing business goals to maximize the return on investment that will be gleaned from future data analytics.
Before data analytics can be presented in a KPI report, the data must first be prepared and processed. Data preparation is the process of sorting data, and removing irrelevant data prior to the beginning of analysis. The goal of data preparation is to define the organization’s goals, identify the relevant data sources, and combine the datasets that will answer the questions required to reach each particular goal.
AI & Analytics
Managing extremely large sets of data can be impractical. Artificial intelligence is used in analytics to sort through data much more efficiently than a human could analyze it. Another benefit to AI is that it can analyze incoming data streams in real-time, as opposed to weekly or monthly analysis. Using machine learning to process your organization’s data can quickly highlight trends, and transform them into actionable data.