Can Augmented Analytics transform your Organization?

In every industry, today’s organizations require good data to make informed strategic decisions. Earlier, the complexity of data analytics belonged to data professionals, as they were aware of the know-how, software, and expertise that are required to execute the data analytics lifecycle, along with data exploration and preparation, model design and development, and insight generation and dissemination.?

However, the whole process was manual and tedious, as each project took weeks and longer, and other teams had to wait to get the correct information and further make decisions and actions that would benefit the business's future.?

Gradually, with the introduction of highly competitive digital environments, businesses needed a better solution to make faster decisions with deeper insights. However, most of the data science team could not scale their operation fast enough to keep up with the demands of data analyses, big data, and other large, complex data stores.?

That’s where an organization needs to depend on tools such as augmented analytics.

In today’s exclusive AI‐TechPark newsletter, we will take a quick look at how augmented analytics can revolutionize businesses across numerous industries by streamlining data-driven decisions.?

Augmented analytics come in handy for data professionals as they harness artificial intelligence (AI) and machine learning (ML) to track, identify, understand, and act on important tasks, inherently knowing the best action to be taken to accomplish them. This technology further manages and understands data faster and easier through automation, natural language capabilities, and algorithms that enhance the key steps to creating an analytics life cycle.?

In this digitized landscape, large enterprises are looking for ways to reduce the analytics loads for their data teams, adding ability and value beyond conventional reporting, which broadens the use of augmented analytics to analyze large datasets.?

According to a survey, it was observed that organizations that have fully implemented technologies such as augmented analytics, AI, and ML in their daily business operations have seen success in finding relevant data quickly and making data-driven decisions for the company’s ROI.?

However, augmented analytics are not limited to data elites but can also be applied to numerous use cases across various industries. For instance, earlier in the banking sector, targeting the right customer was a tedious task, as each customer had different banking requirements. But gradually the industry understood that they lacked proper data infrastructure, which included demographics, gender, age, and income source, and they started using augmented analytics to automate the analysis of their high-volume data and ask deeper questions to discover which age group was likely to engage with the bank services.?

The marketing sector has also been revolutionized by augmented analytics, as it provides B2B marketers with insights from their marketing and sales data. The technology further uncovers valuable information about clients optimizes ongoing campaigns swiftly and maximizes the ROI of their marketing activities.

Data is known as critical fuel to generate better customer experiences, more efficient operations, and new revenue streams. Therefore, organizations across the globe are trying their best to analyze data through augmented analytics, which aids them in refining complex algorithms, further enhancing professional analytic abilities, driving digital transformation, and developing businesses that are ready to face this change.?

This technological change brings more competitive and impactful efforts in the business world, as it broadens the use of analytics and reaches a lot of professionals who are less comfortable working with data.