Businesses that seek to leverage data for decision-making and problem-solving need to invest in AI to acquire more value from existing data. AI (Artificial Intelligence) is a group of technologies that utilize computer science programming to replicate human thoughts and actions. It does this by analyzing data, anticipating and solving problems, or adapting to particular tasks.
AI makes data analytics even more efficient and accurate as it excels in deriving insights and identifying patterns in large data sets. It can also use this information to make predictions about the cause of specific outcomes. Therefore, it is an ideal technology for businesses that rely on data analytics for decision-making. Here are a few ways that AI will improve data analytics.
1. Automation
Data analytics can be a time-consuming and expensive process. Artificial Intelligence will make work easier by automating processes, saving time and money. It also improves the efficiency of data analytics. Among the crucial aspects of data analytics that AI will improve is data analysis which includes data preparation and insight generation.
AI technology can analyze data independently and perform automated actions based on the results. It can also provide insights to users, who can then use the information to decide on the appropriate course of action. AI will automate data extraction, transformation, and loading process and provide valuable insights much faster. The same tasks would take days or months if performed by data scientists.
Besides automating data analysis, AI adds to data analytics by automating report generation, which enhances the usability of data analytics. While Machine Learning generates all the insights, natural language generation (NGL) converts the insights into human-readable formats that make data easy to understand.
2. Increasing Accessibility
AI increases accessibility and democratization of analytics by allowing the querying of data. Data analytics users can interact with data, ask questions, and obtain answers in real-time by leveraging natural language generation (NLG) supported by natural language query (NLQ). AI takes queries by users in the form of natural language and translates them to machine language before producing meaningful insights in an easy-to-understand manner.
By enabling queries, AI empowers everyone to utilize analytics products and explore their data deeper. This boosts data literacy and reduces the workload of data scientists, allowing them to concentrate on other essential tasks. It can also help businesses reduce their expenses by eliminating the cost of hiring expert data scientists to analyze data with business intelligence tools.
3. Widening the Scope of Analytics
Previously, companies could not use unstructured data and personally identifiable data in their analytics. Also, excel and other traditional analytic tools are not as effective in handling unstructured data such as images and audio.
AI widens the scope of analytics through natural language processing which enables text analytics, transcription for speech analytics, and computer vision which makes video and image analytics possible. Semi-structured data such as invoices, order forms, and receipts also hold tons of company data which can help understand a business better. Data extraction tools based on deep learning allow organizations to extract helpful information from semi-structured data and gain more business insights.
As the demand for data analytics grows, the protection of personally identifiable data is also increasing, leading to an increase in the need for anonymized data. With AI, companies can generate synthetic customer copies and run simulations that enable them to improve their products and services. Although the synthetic data are anonymized and generated by machines, they adhere to the distributions of the customers’ personally identifiable data. Companies can analyze personally identifiable data without going against privacy requirements.
The Bottom Line
With the vast volumes of data that businesses produce, it can be challenging to use and manage data optimally. By using AI in data analytics, companies will enjoy faster and more accurate data analysis, boost productivity and optimize operations.