Augmented Analytics: How It Will Impact the Enterprise

Everyone has heard the saying that “money makes the world go around.” Although a lot of people might accept this without a moment’s thought, it is not necessarily true. Remember, even without complicated money systems in the past, the world still went around. In reality, one thing that never left us was data. From prehistoric times to the present day, data has been an essential element of human life.

Data is what resulted in knowledge, knowledge is what led to advancement and innovations, and advancements and innovations are what brought us to where we are today. From the first fire ever started by man to the technology we harness today, these all resulted from a breakthrough in the way we understand data and develop knowledge out of it.

Contrary to what a lot of people might think, data is not concentrated on research and development initiatives; all industries utilize large sums of data. Additionally, one of the most data-heavy industries of the present day is the business industry.

Business industries thrive on data. They are heavily reliant on data to help in mapping out their business direction. Data helps businesses make guided decisions according to the changing market trends. As such, any development in the process of data collection and analysis can be a game-changer that impacts entire enterprises. Coincidentally, augmented analytics is now making waves, threatening to drastically change the way how data processing works.

What Is Augmented Analytics?

As said earlier, businesses run on data. However, data can never be useful to an organization unless they can extract the meaning from it; and this is where a lot of businesses struggle. In the process of knowledge creation, understanding the meaning behind lumps of data is difficult. Sometimes, with the difficulty of manually detecting trends in data, a business can be stuck and unable to identify significance in their data collected. This leaves a business unable to harness the benefits of data in their daily processes.

Augmented Analytics

Augmented analytics is a new way of data processing that uses the power of machine learning (ML) and artificial intelligence (AI). In the process of augmented analytics, data will be taken from raw data sources and analyzed through ML and AI processes. Through the use of statistical and linguistics technology, augmented analytics can improve data management performance. This will then be converted into a report that is easily understandable for humans. With this new process, several benefits are presented.

How Will Augmented Analytics Impact the Enterprise?

1. Augmented analytics minimalizes human error.

Let’s face it. In a lot of technical matters, the chances of human error are highly likely. Whenever data interpretation is done by a human, the chances of creating an inaccurate and misleading analysis is an error that needs to be taken into consideration. Biases, miscomputations, and faulty analyses can’t be prevented. However, in augmented analytics, machine learning takes over the different tasks that are highly susceptible to error and misrepresentation. This technology makes crucial data accessible even without the presence of a data scientist. However, this breakthrough technology does not replace humans, rather, it supports them in creating better and more accurate interpretations of large data sets. This results in the faster creation of important information.

2. It helps hastens the process.

If an individual can only analyze a portion of data at a time, augmented analytics can analyze data on a large scale. Instead of taking data by parts, it simultaneously takes large chunks of data from a raw data source and comprehensively summarizes it for data analysts to further examine. Given how essential data is to business processes and advancements, augmented analytics can help companies stay up to date with the different market trends. Through their updated data, they can be dynamic in forwarding advancements in their products and marketing strategies. This also helps them adapt to the different interests of their market base.

3. It allows the focus to be shifted on much more difficult analytical tasks.

With the new capabilities of augmented analytics, the day-to-day needs of the business community no longer need to be allocated to different analysts, data scientists, and other internal IT staff. There are a lot of more complicated data analyses that need to be done in the business industry. Often, due to the heavy workload, analysts lack the time and resources to lend their support to strategic issues. With the daily analytical tasks out of the way, they can now focus on much more important tasks.

4. It automates a lot of the manual processes.

Before a data scientist can dive into the process of understanding data, they first need to undergo a manual process of exporting data sets. They look at countless records to spot trends and different business insights. However, given how wide the raw data may be on this first level of analysis, this may take hours and hours of work. Augmented analytics removes the need for manual sifting. It can directly export, structure, and organize raw data sets through carefully programmed machine learning and artificial intelligence. This way, a skilled data scientist may allocate their work to intensive analytical tasks that are too complicated for augmented analytics.

5. It empowers a lot of individuals to understand data analysis.

Prior to the rise of augmented analytics, the knowledge of business insights was centered around experts and data professionals. Often, the process was too complicated to be understood by a layperson. However, given how augmented analytics takes over the process and presents the data in a highly understandable manner, a normal individual may now understand the ins and outs of regular day-to-day business information. This empowers people to adapt to the different business actions that need to be done, with or without the help of a data professional.

6. It allows for more in-depth data analysis.

Whether we like it or not, there are times where humans can never really outlast a machine. After all, humans do not run on fuel or electricity. Given that machines don’t really need rest, they can work on data analysis 24/7. Augmented analytics is programmed to constantly stay active. Its algorithm prompts it to refine its patterns and look for new ones at any given moment. Unlike humans, there is no rest in the process of data analysis. It is always real-time, giving the most in-depth and accurate data analysis possible.

The Takeaways

We are in an age of information where data is constantly flowing, and knowledge is being created at every given moment. Right now, with the high-stake competition, business is not as simple as it used to be. High-quality products and good service are not enough. It is the goal of businesses to stay on top of the game by always being dynamic and adaptive to the different changes in the market. After all, business is not about what you have to offer, but about what people wish to avail of or purchase. In order to be ahead of the competition, businesses need to do what they can to understand the needs of their consumers. With the advancements offered by augmented analytics, this can all be possible.