Most organizations are still adapting to the changed business requirements brought about by the pandemic. Even though the situation currently seems less severe and there are long-term changes towards a new normal, day-to-day business isn’t settled yet.
Some organizations are grappling with a decline in orders, while others are struggling with supply chain disturbances or are still adapting their operations to the changed requirements. A recent study established that organizations are still working on their data foundations and are working to place themselves in the long term.
Businesses are addressing the primary causes of their challenges and are working towards establishing a holistic data-driven culture. Companies are watching emerging tech trends to discover the latest trends that’ll give them an edge over their competitors.
This article covers five emerging trends in BI that are driving its implementation.
What Are The Top 5 Emerging Trends In BI?
Whether you’re planning to install business intelligence tools or already have, understanding emerging trends in BI is essential. Monitoring trends can assist you in making the most out of them and navigating BI digitalization’s disruptive forces. Here are five emerging trends that are shaping the BI industry’s future:
1. Automated Machine Learning
Also referred to as AutoML, automated machine learning is a tool that allows business analysts who don’t have a strong machine learning background to build machine learning models to solve business problems. This technology gives business analysts robust ML and AI problem-solving features without needing experience.
More businesses are embracing AutoML tools as they can handle the heavy information lifting required to get to the core of performance. Most of these companies have integrated AutoML into Power BI and Microsoft Azure, enabling them to use these advanced tools. ML algorithms can help identify factors limiting your brand’s health. AutoML identifies the underlying currents limiting growth.
In an era of increasing automation, it only makes sense for a business to leverage the advantages of AutoML. Partnering with a BI service provider like Bennyhoff Products and Services (BPS) can help you Integrate AutoML software into your business intelligence tools to help you remain competitive.
The software will help you make sense of your company data and transform how BI is shared across your departments, thus optimizing data-driven decision-making.
Advanced analytic techniques have risen in popularity when developing business solutions; with AutoML, businesses can make the most of these capabilities with little ML experience.
2. Embedded BI Applications
Embedded BI refers to integrating data visualizations, dashboards, and reports inside an application. A BI platform usually manages and displays the data placed directly in the app’s user interface to enhance decision-making and data usability.
The embedded industry sector is experiencing substantial demand from large, medium, and small enterprises primarily due to data analysis, reporting, management, and visualization offerings.
The increased mobile BI adoption with cloud computing tech has also contributed to the embedded sector’s growth. The emergence of data-driven businesses has also contributed to the increased use of embedded applications.
As a business, you must create a collaborative outside-in approach to innovation by opening your analytics to your customers, partners, and the broader ecosystem. You should embed analytics by inserting dashboards into a workflow and alerts to micro insights that can lead to enhanced decision-making.
Embedded BI applications provide businesses with a modern way to present data, ultimately boosting satisfaction and user engagement.
3. Data Security
Data security refers to protecting company data and preventing data loss via unauthorized access. This includes protecting data from attacks that can destroy or encrypt data or that can corrupt or modify data. Data security also entails ensuring that information is available to authorized individuals.
Data security is a primary concern for most companies in the digital era, as many cyber attackers are looking for an opportunity to strike. There’s always a chance of a successful cyber attack if a company hasn’t implemented effective security measures. Since consumers know the value of personal data, they work to mend all security loopholes.
As a business, the more you share APIs and data and embed trigger actions and analytics, the more you need to protect against failures. BPS can help you use Power BI methods like sensitivity labels and row-level security. Row-level security restricts access to data based on a group of people, while with sensitivity labels, an owner can apply a label on reports that define a report’s sensitivity.
When implemented well, solid data security approaches will protect a company’s data against cyberattacks and against other threats and human errors, which are the main causes of data breaches.
4. Data Discovery/Visualization
Data visualization refers to data representation through graphics like animations, infographics, plots, and charts. In contrast, data discovery refers to locating and identifying regulated or sensitive data to protect or remove it securely.
Business agility is the hallmark of a successful enterprise, and data discovery is part of its foundation. Data discovery gives companies an overview of their operations so they can understand and address any challenges they face.
Data discovery has risen in popularity as companies have started treating data as an asset and the data they collect from their operations and customers has the potential to give them a competitive edge. Data discovery allows companies to turn BI into a competitive advantage, whether in efficiency gains, customer experience, or product innovation.
As a business, you should leverage data discovery to solve and identify business challenges. By assessing data, you can find patterns and trends that can assist you in improving your operations, services, and products. You can also use insights like market trends and customer behavior to make better decisions.
Data discovery can help identify correlations, outliers, and trends and create reports and visualizations that companies can use to communicate findings to stakeholders.
5. SaaS and Cloud Analytics
The most basic cloud computing site, SaaS, is hosted, web-based or on-demand software. A vendor supplies the same site as-is to various businesses, and the vendor is responsible for segmenting users’ data and upgrading and maintaining the site.
Cloud analytics is a delivery and service model for hosting that deals with the computation or analysis of business information using cloud technologies. Most businesses opt for SaaS and cloud-based BI technologies as they offer them the potential for reduced costs, increased flexibility, and faster deployments compared to conventional on-premise BI software.
To increase your competitive edge, consider working with BPS to implement SaaS and Cloud-based BI for timely and accurate forecasting and real-time data assessment.
Cloud-based solutions are more sophisticated in handling security and enable safe information transfer from various sources without compromising data security.
What Is The Future Of BI?
The BI sector has come a long way since its inception in the 19th century, where data-driven decisions are made using BI technology rather than hunches. Businesses use BI to understand customer behavior and enhance their bottom line. The next generation of the BI industry promises to be conversational, customizable, approachable, and accessible.
BI’s future is proactive; companies will have data before asking for it and revealing insights you never knew you needed. Future BI will empower everyone in the company to understand and harness the power of information to make business decisions ethically and intelligently.
Businesses should develop systems to help them adapt to the changes to confront the ever-changing BI landscape. Contact BPS for tools like Power BI to increase efficiency and enable everyone in your company to make data-driven decisions.