Traditional BI, Augmented Analytics, or Modern BI/Analytics?
Whether your business is planning to acquire a business intelligence (BI) or augmented analytics tool for a first-time installation or looking to upgrade an existing system, the decision starts with the ‘what’ of the solution. What kind of solution will best fit your needs for infrastructure, integration, user requirements, pricing, upgrades etc. and what kind of approach, features and functionality will be most suitable for your business.
‘When considering a new or upgraded business intelligence or advanced analytics solution, it is important to look at your enterprise requirements to accommodate existing technologies and infrastructure, business processes and models and user needs.’
A Recent Study reveals a number of considerations to be included in your choice of BI tools and analytical platforms, including:
- Zero footprint: 100% web-based, no client-side installs or downloads required
- Support for role-based reporting and dashboards
- Support for mobile Business Intelligence
- Communication features like notes, comments, and likes
- Updates in real-time: your dashboard is always up to date
- Basket, advanced and predictive analysis
- Support for machine learning and generative AI
- Usability: ease-of-use and ease-of-learning
- Insights (graphs, definitions, et cetera) that are reusable across BI applications
While this study carves out what it considers to be the optimal analytics framework and platform, some of all of these considerations may not apply to your business needs.
When reviewing the various iterations of analytics frameworks and platforms, you will need to understand the following capabilities and structures. Understanding how each of these approaches works and what advantages and limitations they include will make it easier for you to choose a solution and approach to suit your needs.
Augmented Analytics
Today’s augmented data analytics incorporates artificial intelligence (AI) and machine learning (ML) to streamline, automate and improve the process of data analysis, so business users can more easily gather, interact with, select and report on data, simplifying data prep, insight and collaboration and allowing your team to explore data in a way that is meaningful to them.
Augmented analytics uses machine learning, natural language processing (NLP), and algorithms to easily analyze and manipulate large datasets and reduces the time needed for processing, thereby allowing business users to leverage analytics in their day-to-day workflow and freeing Data Scientists to perform more strategic tasks.
Benefits of Augmented Analytics
- Streamlined data prep and analytics
- Optimizes business user and data scientist time and effort
- Faster, more insightful decision-making
- Increased operational efficiency
- Democratized data analytics
Traditional Business intelligence
Traditional BI Tools use conventional analytical techniques and technologies to collect, analyze and present data. These systems typically rely on a centralized data source and a selected set of formatted reports. Users leverage data extraction, transformation and loading tools (ETL) to extract data from a data warehouse and online analytical processing (OLAP) tools to analyze data. Reports and visualization are typically delivered through a dashboard with standard key performance indicator (KPI) software to monitor metrics.
Benefits of Traditional BI Tools
- These tools provide support for a range of data types and data sources
- IT and/or data scientists can create standardized reports and models to address business and user needs
- The enterprise can maintain and control data sources on-site
Modern BI Tools and Augmented Analytics
When an organization integrates the use of modern BI tools with more advanced augmented analytics it can leverage artificial intelligence and traditional tools to satisfy the needs of a diverse set of users, business units, etc. Modern Business Intelligence technologies integrates more sophisticated features to bring analytics to all users and allow them to choose the tools that best suit their needs in a self-serve environment with automated data preparation, fast and easy data access and insight, Natural Language Processing (NLP) that allows users to ask questions using common language and receive answers using visualization techniques.
Benefits of Modern BI Tools and Augmented Analytics Combined
- Sophisticated self-serve analytics suitable for business users with limited technical skills
- Real-Time insights and reduced time-to-decision
- Monitoring and managing of trends, anomalies and other factors that impact results
- Collaboration and data democratization with unique tools to suit every user
‘When reviewing the various iterations of analytics frameworks and platforms, you will need to understand the following capabilities and structures. Understanding how each of these approaches works and what advantages and limitations they include will make it easier for you to choose a solution and approach to suit your needs.’
When considering a new or upgraded business intelligence or advanced analytics solution, it is important to look at your enterprise requirements to accommodate existing technologies and infrastructure, business processes and models and user needs.
Contact Us to discuss the unique needs of your organization and your users and find out more about Smarten Technology. The process of choosing the right Analytics Solution for your busine is crucial and must include a careful assessment of your needs. Explore our White Paper: ‘Enabling Business Optimization And Expense Reduction Through The Use Of Augmented Analytics,’ and our article, ‘How Does Low Code And No Code Development Support BI Tools?’
Original Post : Which BI or Analytics Tool is Best for My Business?
