Businesses around the world are considering or continuing to favor the shifting trend of digital transformation, due to the ever-increasing generation of data in terms of complexity and volume. The amount of data they deal with makes data analytics an essential component of business development. The companies are continually attempting to out-perform their peers by staying abreast of the on-going changes in the business analytics market.
In order to sustain in this digital transformation journey, it is imperative for an organization to fulfill the demand of being market-readiness, timelines by altering the time-intensive manual analytics, also known as traditional analytics, a process that prepares and analyzes data to interpret the results and create insights. This analytical model brings along noteworthy challenges to the companies that are endeavoring to manage the constant burst of data generated over multiple platforms.
To tackle this ever-growing concerns, data analytics market has disrupted a new paradigm that provide assistance to data scientists by augmenting their skills with automation provided by machine learning, and artificial intelligence (AI) techniques to expedite and simplify the entire analytical process, called as augmented analytics, which has started gaining traction as a field, as many organizations are looking forward to integrating its advantages in their business. Majorly, companies from sectors, namely retail, pharmaceutical, manufacturing and others that are undergoing or strategizing to survive in this digitally transforming business world, are beginning to shift their use to this rapidly demanding technological system. Thus, Inkwood Research assumes that this emergent field will expand broadly with regards to understanding and usage in the coming future.
The “smart data discovery” term was formally initiated in the year 2017, and is influencing the industries as a powerful differentiator. The organizations are constantly focusing on building models and integrating data to easily automate the task of achieving clear and actionable insights. In this situation, augmented analytics is a next-gen alternative that delves much deeper and iteratively accomplishes the data-to-insight-to-action activities, such as preparing, deciphering patterns, building models and distributing and utilizing the data findings. It also saves time and resources both by generating actionable, predictive and prescriptive guidance. Thus, enterprises are recommended its adoption, as its capabilities are maturing.
Augmented Analytics Transform Big Data into Smart Data
Augmented Analytics is a powerful mechanism in providing business owners to be more receptive and agile. Thus, its key benefits are changing the practice of conventional business models, namely;
• Speeds-up the process of data discovery and preparation
• Accurate, unbiased, cost-efficient and less time-consuming solutions for decision-making
• Easy access to the actionable insights across the organization
• Simplify the overall data analytics process for less business-savvy operators
• Improvise products, services, and other aspects of the business
• Prompt smart data insights boost productivity and analytics, thereby have a positive impact on the overall business turnover
• Provide more time to focus on strategic issues and crucial projects
Top Three Benefits of Augmented Analytics
From the above list, let’s explore the significant benefits that are genuinely disrupting your business.
- Simplification of Data Analytics
Through the process of data preparation, augmented analytics helps in detecting impactful signals from the business models. It provides assistance to the inept business-savvy data executives that are unable to decipher its findings. With “natural language generation” software, data scientists are not required to determine the accurate algorithm to get results. Augmented analytics works as a toolset and runs multiple algorithms on the data in a unified format to perceive outliers and patterns. In other words, it democratizes the generated learning, making it effortlessly usable for business executives to determine complex insights.
- Speed-up the Data Discovery Process and Preparation
Data preparation can be a complex and cumbersome effort when performed manually. Hence, when a pile of records is required to comb through, data scientists would literally require months for a presumably simple task like this. In this fast-evolving digital world, it has become essential to cognize customer’s requirements. But, data generated from legacy systems did not reap enough fruit due to discrepancies in various fields, and unifying them in one format was also intimidating. Nevertheless, with the deployment of augmented analytics, equipped with ML algorithms and data preparation techniques, enterprises can clear the data in no time by automating the process by these BI tools.
- Facilitate Communication across the Organization
Once the actionable outlines have been established through the learning achieved from the generated data, they are needed to be shared with executives. The traditional ways to accomplish this, additionally burden the executives. But, the augmented analytics tool replaces the human efforts into AI and translates the required reading into natural language. Hence, this level of powerful learning, facilitates data-driven decision-making and adoption across the overall organization.
Significant Importance of these Benefits to Digital Businesses
While competing in the Digital Age, it is well understood that data is oil to an organization. Thus, the underlying complexities integral in traditional analytics processes, creating many roadblocks, have provided the augmented analytics market with potential opportunities to gain traction in the analytics of enterprises. Moreover, there is a lack of professional data scientists that practice data science, with a keen understanding of business models and operations. Also, today, time is money, yet, data scientists spend a large percentage in manually preparing data, such as cleaning and labeling. This shortage of time and capabilities is well-taken care with augmented analytics, which utilizes the mined data to create actionable plans and understanding.
Move Forward with Augmented Analytics
The augmented analytics market is still to make its mark on a global scale. Currently, many enterprises are not adopting it as an end-to-end process, but, trying one piece of the puzzle at a time, which is an excellent way to start. Inkwood Research expects that in the coming years, this scenario will witness a change, and enterprises will prefer to automate the entire lifecycle of data analytics. Also, with the significant benefits to consider: democratization, broad adoption and speed, organizations will equip their understanding with customer’s requirements, take necessary actions and improvise their business process to position themselves in the race of success – today and in the future.