Today, the world is all about Internet technology and artificial intelligence. Deliberate time is not given to business analysis or statistics. The lack of time and the constant need for well-presented data have given birth to a different field of study – business intelligence. Business intelligence is becoming a challenging concept that is needed everywhere.
Analytics and BI
Business Intelligence is a field that explores processes and techniques, including architecture and technology, for the conversion of raw data into information to drive higher profits into the business.
In recent years organizations moved towards creating a culture of data by utilizing several emerging technologies in AI and beyond. Organizations started adopting several emerging trends across the technology, process and people aspects of BI. Though many companies are still adapting to changing requirements due to the COVID-19 pandemic, most businesses adapt to the latest trends to sustain business continuity and remain competitive.
The BI and Analytics survey 2022 result issued by an industry analyst and consulting agency, BARC –Business Application Research Centre highlight the following focus areas:
- Visual analysis
- Cloud BI
- Data preparation
- Operational BI
- Embedded BI
The Analytics and BI trends count but are not limited to the following:
- Advanced Analytics / Machine Learning / AI
- Augmented Analytics
- Embedded BI and Analytics
- Agile BI Development
- Cloud for Data and Analytics
- Data Catalogues / Discovery/Visualization
- Analytics Teams / Data Labs
- Data Governance
- Data Preparation by Business Users
- Data-Driven Culture
- Decision Automation
- IoT Data and Analytics, etc.
These trends are adopted as per business needs.
Some of the frequently talked top trends are listed below.
This technique involves the use of machine learning (ML) and natural language processing (NLP) to enhance data analytics, data sharing and business intelligence and results in simplifying the BI and Data analytics process for business users and citizen data scientists.
Organizations can enter raw data source information into this platform which will then scrub, parse and return business data for analysis. The use of ML and NLP enables enhanced analysis tools to organically understand and communicate data as well as to capture valuable or unusual trends.
The estimated augmented analytics market, as per the Globe Newswire, would reach $13 billion by 2023.
The embedded analysis gives more power to end-users. It gives the client more ability to interact with information.
Embedded BI helps reduce the workload on analytics teams, gives end users a faster way to gain the insights they need and allows analytics teams to focus on new products that help businesses grow and differentiate.
Predictive analytics is a form of advanced analytics that uses both new and historical data to forecast activity, behavior and trends — has grown in prominence alongside the emergence of big data systems.
The predictive analysis involves the application of statistical analysis techniques, analytical queries, and automated machine learning algorithms. Prescriptive analytics seeks to determine the best solution or outcome from a variety of choices, taking into account known parameters.
Artificial Intelligence and Business Intelligence
AI is the science that drives machines to operate, usually through complex human intelligence. Artificial intelligence is one of the most trending terms these days. It helps humanize data and make it more accessible to all. Collaborative and self-service BI is making it easier for users to find insights both together and alone.
AI is becoming more and more mainstream, with NLP and automation increasing in popularity. Companies adopt powerful artificial intelligence tools for process automation to evaluate and make insights more accessible to all.
AI and BI are often considered to be technologies with little overlap because BI is primarily retrospective, while AI is all about the future. No wonder AI is expected to be the New BI.
IT operations and other teams can improve their core processes, decision-making and functions with AIOps solutions and perform improved analysis of data volumes. IT leaders are looking for AIOps providers that would enable cross-team collaboration through the integration of end-to-end digital experience, data correlation and IT operations management tool chain.
Accelerated SaaS / Cloud Adoption
In recent years, most businesses have wanted to migrate to the cloud and take advantage of all the benefits of cloud-based BI, either by hosting it privately or publicly in the cloud or by subscribing to a software-as-a-service (SaaS) solution.
According to the Dresner Cloud Computing and Business Intelligence Market Report, 2020, post-COVID-19, 95% or more of the enterprise software vendors will consider Cloud BI essential, as each organization is now distributed.
Agile BI Development
This approach involves software development methodologies used in BI and analytical processes to establish flexibility, improve functionality, and adapt to new business demands in BI and analytical projects. It is intended to reduce the time-to-value of traditional BI, improve the outcomes of BI initiatives and adapt to the changing demands.
The agile BI approach differs from the traditional BI methodologies. It enables enterprises to keep pace with the market’s changing demands by combining new and emerging technologies and architectures.
Businesses will look to Cloud and Augmented BIs as part of their modernization strategies as their employees migrate to remote work, in the years to come, after overcoming the pandemic.
Besides Data literacy, businesses need to establish and refine data governance policies to protect themselves, their users, and their data. Companies across all industries should strive to make effective use of the insights provided by BI as their data becomes more complex and diverse. Contact Kockpit Analytics to learn more!
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