Discovering the value of augmented analytics has triggered rapid growth in many businesses. Where conventional analytics gives companies access to their data easily, augmented analytics has helped business executives find relevant data, investigate the results, and quickly deliver insights based on their business’ current condition and performance. Knowledge gained from augmented analytics has also accelerated analytical processes, helping analysts and operators gather organizational data from all sources, perform their research, and prepare findings within a shorter time frame. This has enabled leaders to make all kinds of effective business decisions, from identifying areas of the business that require improvement, to mitigating risks, to capitalizing on product trends, and beyond.
Bold BI aids in augmented analytics by allowing business users to predict future outcomes based on current analysis. Let’s dive into the following topics to better understand augmented analytics and how the insight it provides can boost business performance.
- What is augmented analytics?
- Significance of augmented analytics
- Augmented analytics use cases
- Challenges of augmented analytics.
- Best practices for augmented analytics
- Augmented analytics and Bold BI
What is augmented analytics?
Augmented analytics is the application of artificial intelligence (AI) and machine learning (ML) to data analytics. It lends support to data preparation, analysis, and insight derivation, without needing data scientists on hand to transform data into decisions.
Significance of augmented analytics
Augmented analytics helps various businesses in many ways. Its techniques allow data operators to increase their analytical output and produce more accurate results for stakeholders. It also allows leaders to spot barriers to the business’ success earlier and make the right choices regarding each issue. Let’s discuss the following ways that business owners can benefit from augmented analytics:
- Make effective data-driven decisions
- Better understand business trends and patterns
- Enhance business productivity
- Identify new business opportunities
Make effective data-driven decisions
Making excellent data-driven decisions demands one to have complete information concerning their data. With augmented analytics technologies, you can track data from all sources in your organization, giving you a clear picture of your employees, projects, sales—anything and everything that you gather data on. The application of machine learning to analytics gives business leaders greater insight into the context of their data. This allows them to determine the types of changes that will lead to massive improvements in the business and pursue them with confidence. The aid of augmented analytics enables leaders to acquire real-time data-driven insights that help them determine future business strategies.
Better understand business trends and patterns
Many business leaders do not understand trends and patterns in their industry. They rely on lucky guesses and coasting on the success of their competition. As a result, they end up selling their products to the wrong customers, which in turn inhibits their sales, forces them to sell their products and services at a lower price, and thus run at a loss. Having a firm grasp of trends and patterns in the market, sales, and clients’ purchases is the most assured way to avoid business-related dangers, maximize revenue, and retain customers. Augmented analytics makes this simpler by allowing business leaders to analyze their sales data more confidently and gain knowledge about their clients, market trends, and sales trends. With the right information in hand, businesses can keep the right inventory, meet the needs of existing customers, and pursue highly qualified leads.
Enhance business productivity
Augmented analytics helps business owners and managers enhance their business’s productivity. It provides them with a deeper understanding of the company’s productivity level and why it is what it is. Then, they can look for ways to increase it. In the process of their research, they might find that employees recognized for certain achievements tend to be more productive, and a more thorough contribution recognition model could be implemented to motivate employees. By aiming augmented analytics toward employee feedback and complaints, managers can identify and address common issues that have harmful effects throughout the business. Such actions enhance the overall performance of the company and improve its productivity.
Identify new business opportunities
Deploying augmented analytics helps business leaders identify which products and services are trending higher in demand in the market, allowing them to capitalize on this insight. Further, augmented analytics can give business leaders a better idea of why customers choose their products over competitors,’ and can then emphasize those differences in marketing campaigns and sales calls. With the deeply contextualized information provided by augmented analytics, a business can better fill its space in the industry and make well-informed decisions to acquire new clients.
Augmented analytics use cases
Augmented analytics has helped businesses in very different industries change their outlooks both internally and externally. By allowing leaders to harness the power of data in their daily work applications, they are able to extract insights that help them make crucial business decisions. With the augmentation of analytics technologies via machine learning and artificial intelligence, companies gain powerful tools to beat their competitors and increase their profitability. The following are some of the top industries benefiting from augmented analytics today:
The hospitality industry includes hotels, tourism destinations, travel accommodations, and much more. Due to the wide range of activities in the industry, tracking all the data flowing in and out of a single company in the industry can be a monumental task. In the case of a hotel, there is not only a need to track data on daily bookings by priority, booking sources, occupancy rates, and customer satisfaction rates, but also a need to ensure that the company is productive enough to facilitate the business’s long-term success. Augmented analytics helps hotel managers track the company’s immense amount of data, giving them a head-start on the vital analysis that can illuminate the path to continued business success.
Sales data visualizations gives sales teams actionable insights about their complete financial status to help the company calculate current income against company expenses to determine its revenue performance. This would not be possible without the proper analysis of data. This is where augmented analytics chips in. It helps analysts and operators in the company more quickly analyze data concerning the company’s financial health and provide an accurate, wholistic picture of it. Identifying low-profit areas in the sales department through analytics allows management to redistribute resources to areas of proven success, regardless of previous investment. The evidence brought forth by augmented analytics gives sales leads sound reasoning for their decisions. This also boosts their confidence, helping them reach their financial and other benchmark targets. Furthermore, sales leads can apply augmented analytics to their department’s historical data to find what sort of model closely matches their past sales and use it to predict future revenues.
Another important industry that needs analytics to run its operations properly is healthcare. In this industry, analytics are used in hospitals’ daily applications to improve their workflow and patient experience. Augmented analytics helps healthcare industry leaders track, monitor, and analyze diagnostic trends in different hospitals to create community awareness of the most common diseases and derive insights that will help them provide proper diagnoses to patients. It also allows doctors to analyze their patients’ vital signs, lab results, and readmission rates to determine the efficacy of their services and identify better ways of helping patients.
Augmented analytics helps firms in the retail industry keep accurate inventories in their warehouses and reduce the cost of maintaining them. Insight into products currently selling well on the market allows retailers to better align their warehouse capacity with what is likely to bring in revenue. They can reduce the cost of stocking warehouses by storing only proper inventories to be sold or shipped in the short term. Drilling down, augmented analytics also helps store managers keep accurate records of their shelf inventories to avoid problems with stocking.
Challenges of augmented analytics
Let’s discuss some of the challenges to adopting augmented analytics.
Providing quality data to your augmented analytics solution means that you must first understand the composition of your data. Organizations adopting augmented analytics face difficulties in educating intended users about their platform’s analytics models and capabilities. This is due to a variety of reasons. Often, less-technical users fail to understand properly the data they want to analyze. Though some automation is often at play in augmented analytics, it may not be able to do what business users expect immediately upon implementation. Data scientists and others within the company with advanced domain-specific knowledge may need to provide guided instruction to colleagues before an augmented analytics platform is usable on a day-to-day basis.
An organization’s productivity with augmented analytics depends on its analytics platform’s capabilities. An organization deploying augmented analytics, when considered in conjunction with the volume of data involved, must have the right IT infrastructure to handle the computational power required by augmented analytics.
Implementing augmented analytics requires properly filtering data to facilitate the removal of all information irrelevant to the problem being analyzed. This allows the produced results to be relevant, more reliable, and more accurate. Some companies may find it time-consuming to test their data regularly to ensure results are properly relevant.
Implementing augmented analytics techniques such as artificial intelligence systems require data as the foundation of the system. Therefore, the quality and reliability of data need to be considered as they directly affect the reliability of artificial intelligence products. This can be a challenge to small businesses as they need to invest in data governance practices to successfully embrace artificial intelligence in their software applications.
Best practices for augmented analytics
In the remainder of this article, I will discuss some of the best practices for effectively implementing augmented analytics in your business.
Embrace data-driven decisions
Establishing data-driven decisions as a core tenet of the business makes the adoption and consumption of augmented analytics easier for departments to get on board with. By frequently tracking data and monitoring the results of the data-driven decisions in your organization, you can reflexively prove and reinforce the value of augmented analytics.
Encourage teamwork and cooperation
Encouraging wide use of augmented analytics in your organization requires removing obstacles to data access so that more people can use it toward their team or departmental goals. The perception of data analytics as a tool only for the elite in the business must be transformed. Data analytics must be democratized to be a tool for anyone, not just data scientists and analysts. When data analytics is seen as a tool to be used toward any business goal, augmented analytics will be embraced widely and eagerly.
Align key indicators
Deciding which key performance indicators to put under the microscope of augmented analytics helps align the data strategy of the company with its goals. Not all KPIs are created equal. Any metric can be derived, but the ones worth using have to play a role in the decision-making process.
Institutional training to create and increase trust
Every company must train its data scientists and business analysts to use these technologies. Users have to learn how to interact with the analytics platform and validate augmented analytics suggestions. This builds trust and confidence in the tool, alongside the insight provided by their work experiences, knowledge, and judgment.
Augmented analytics and Bold BI
Bold BI is a powerful BI and analytics solution that allows you to glean insights from your complex data by visualizing it using a wide range of widgets. Augmented analytics in Bold BI provides automated data visualization, preparation, modern data architecture, and more to help business users break down their data, identify trends, and make data-driven decisions more effectively. Let’s look at some of the key Bold BI features in detail.
Important features of Bold BI
With Bold BI, every aspect of deployment and routine management, such as provisioning tenants, users, groups, permissions, and scheduling reports, can be fully automated through a rich API layer.
Modern data architecture
Structural data assets and management pose a challenge to flexibility. With Bold BI, you aren’t required to bring all your data into our data store. Also, you don’t need to design a complex system for data integration, nor keep the embedded BI data store in sync with your data sources. With Bold BI, you connect directly to hundreds of data sources and any data warehouse of your choice, such as Excel, SQL, Azure SQL, Amazon Redshift, and more. It helps you connect easily and quickly to the source of your choice.
Visualized data is easily shared, understood, and applied in making informed business decisions. Bold BI provides tools to visualize your data analysis as you desire. It allows the combination of widgets in an intuitive fashion, giving you a complete overview of your data.
Bold BI offers many data preparation features that make your work easier as it does not require you to bring all your data into one store. It allows you to connect to any data store of your choice and use visual data modeling, calculated fields, and advanced data preparation techniques.
I hope you now have a better understanding of augmented analytics, its benefits, and its best practices. Augmented analytics helps you visualize the story behind your data, thus letting you see patterns and trends in your company that reveal actionable insights to help you gain a competitive advantage in your industry.
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