Microsoft, Google, IBM, Amazon, and Oracle continue to dominate the worldwide analytics market. Additionally, Microsoft, Amazon, and Oracle outperform the market for all other vendors. It’s worth noting, however, that the contest between the leading analytics providers is not about “advanced algorithms,” but about Data Quality.
The following are some current trends in business intelligence and analytics:
With collaborative business intelligence technologies, self-service business intelligence has become even more democratic.
Current-generation business intelligence (BI) technologies enable on-the-go analytics.
COVID-19 has compelled a sizable proportion of software vendors to use cloud computing. Cloud-based software-as-a-service use is also increasing.
This year, artificial intelligence (AI) has entered the mainstream, with natural language processing (NLP) gaining traction.
Businesses worldwide have been urged to prioritise data literacy programmes and data-driven cultures.
As a result of stringent data restrictions, businesses are placing a premium on data governance and security.
This DATAVERSITY® paper provides an overview of the 2020 business intelligence and analytics trends.
The Business Intelligence and Analytics Trends for 2022 are summarise here.
Data Literacy is the first trend. (data science in Malaysia)
Businesses have recognised the value-added benefits of data-driven decision-making and actionable intelligence backed by data. They now aim to empower all levels of their organisation with robust Data Literacy initiatives, enabling business users to make educated decisions on a regular basis without the assistance of IT or Data Science teams.
Businesses’ Data Literacy programmes, which have been steadily gaining traction this year, will garner significantly more attention in 2022. This Inside Indiana Business storey outlines why Data Literacy is critical for organisations with data-driven cultures.
Management of data quality is a second trend (DQM)
(data science in Malaysia)
The accuracy of analytics insights is critical, and data quality plays a critical part in this. Erroneous data can result in incorrect insights, which can result in poor business decisions. Thus, what constitutes good data? Accurate, consistent, comprehensive, timely, unique, and validated data is often of high quality.
Data Quality Management (DQM) is the major differentiator of a successful business intelligence platform, and DQM-connected business processes ensure compliance with worldwide Data Quality (DQ) and Data Governance (DG) standards.
Collaboration in business intelligence is a third trend.
Businesses have been pushed to swiftly acquire client data, preferences, and sentiments via social media channels and interactive websites. When such robust data analysis is combine with advanced (collaborative) business intelligence technologies, collaborative business intelligence is achieve.
Collaborative business intelligence is rapidly gaining popularity because it enables rapid data collecting, decision-making, and report sharing. Collaborative business intelligence (BI) facilitates collaborative issue solving and open business discussions using web 2.0 platforms.
Embedded Analytics is a fourth trend.
The global embedded analytics market, according to Allied Market Research Report, is expect to reach US$60 billion by 2023. By virtue of being “resident” within native applications, embedded analytics enables rapid data analysis without requiring data to be move from one software environment to another.
5th Trend: Broad Cloud and SaaS Adoption
By 2021, an increasing number of enterprises will have migrated to hybrid cloud or public cloud and will have begun subscribing to Software as a Service (SaaS) plans for outsourced business intelligence (BI) services.
The cloud BI concept has gained such traction that 95% of software providers support it, and 54% of firms view cloud BI as “very critical” to their businesses (Dresner’s 2020 Cloud Computing and Business Intelligence Market Study).
The following are the primary benefits of cloud-based business intelligence for multinational corporations:
Data stored in the cloud is accessible from any device and from any location.
Maintenance and upgrading services are completely outsourced (stress-free)
Services for data security, backup, and recovery are included.
Cloud computing enables easy service scalability and flexibility.
Processes for simple data management for business clients
Ownership costs are low, yet efficiency is high for commercial clients.
The following is an excerpt from a McKinsey Insights article on how CIOs and CTOs can accelerate cloud adoption for data processing services. This helpful essay explains how to prioritise and align technology expenditures in support of a cloud-based operational model.