Business analytics is going through an inflection point today, and it’s being driven by the need to increase the depth of functionality that these tools deliver without needing a data scientist to support them. Organizations that are driving this inflection point in business analytics tools are also designing advanced technologies, including Natural Language Processing (NLP), support for Hadoop, R and machine learning algorithms into their applications.
Over 100 new business analytics tools have been introduced in the last 18 months. Defining which are the most cutting edge begins with a series of criteria, and progresses through an assessment of each. All of these tools excel at the core dimensions of ease of use, intuitive navigation design and depth of integration points. Each also has the potential to scale beyond doing a core function such as data analysis, and provides deeper insight by supporting advanced modeling.
- By 2020, more than 75% of large and midsize organizations globally will deploy advanced analytics as part of a platform or analytics application in order to improve business decision making according to Gartner.
- State-of-the-art business analytics tools are being developed to provide the most powerful analytics features to business strategies, alleviating the need to hire hard-to-find data scientists.
- The exponential amount of data being generated today with cloud-based Customer Relationship Management (CRM), Enterprise Resource Planning (ERP), Supply Chain Management (SCM) and Service Lifecycle Management (SLM) applications is accelerating. Business analytics tools are needed to find relationships in all forms of data, from unstructured to structured.
- The future of business analytics is being defined by new applications that support data exploration, via intuitive interfaces, and through support for analysis workflows using NLP.
- Providing business analysts with the ability to develop advanced analytics models without needing the help of a data scientist to complete and use them is a cutting-edge development that’ll revolutionize business analytics development for years to come.
- These cutting-edge business analytics tools are enabling more efficient collection, correlation and presentation of semistructured data, making it possible to find entirely new patterns in data sets to build new data models.
What Defines A Cutting Edge Business Analytics Tool?
With the hundreds of new business analytics tools introduced every year, defining which are the most cutting edge needs to begin with a series of criteria that reflects the most important needs of users. Business analysts, manager, and line-of-business staff members are the most frequent users of analytics tools, and during conversations with them, the following criteria were gathered:
- Intuitive, easy-to-use interface that’s customizable by business analysts, not requiring IT to get involved – Business analysts and other power users of business analytics tools value the flexibility and freedom to define workflows, model creation and user interfaces above many other feature requirements they have.The most cutting-edge business analytics tools are capable of guiding non-technical users through the model creation process, while also providing a rich contextual experience regarding data analysis options.
- The option of using a natural language interface to complete analysis, while also providing more API-driven, automated approaches to data analysis – IBM’s Watson natural language interface is the most well-known when it comes to this feature criterion. There are many other smaller, faster-moving companies than IBM that are breaking new ground in the use of NLP today. Amazon QuickSight, Attivio, Endor and Microsoft Power BI are examples of cutting-edge business analytics tools that are actively developing applications using NLP and Natural Language Generation (NLG) responses to queries. These advanced business analytics tools don’t require a data scientist to get them up and running either. Gartner predicts that by 2020, NLP and NLG will be a standard feature in 90% of modern BI platforms.
- Support for advanced analysis algorithms capable of finding patterns in data, and then recommending visualization options– The most cutting-edge business analytics tools build in advanced analytics algorithms, and then prompt users to see how they want to represent the data relationships and insights found. Business analytics tools capable of generating contextualized insights are in high demand, as they save time and generate knowledge not known before.
- Cutting-edge business analytics tools also can combine multiple sources of complex data, scaling from the transactional to the unstructured – During a recent conversation, one CIO remarked that over 60% of his company’s data is semistructured and unstructured. He was looking for cutting-edge business analytics tools that allow for the flexibility of analyzing structured, semistructured and unstructured data without the need for an IT analyst or data scientist.
- The ability to test advanced statistical models iteratively using machine learning algorithms – Another criterion business analysts mentioned when asked for the most important features of cutting-edge business analytics tools is the ability to define test parameters for analytics models and have machine learning-based algorithms seek optimal outcomes.This functionality is often found in higher-end, enterprise-wide BI platforms. Cutting-edge business analytics tools are now beginning to incorporate this functionality into tools and apps designed for mainstream business users.
- Support for large-scale data analysis techniques, including Hadoop, R and others, while also supporting intuitive graphical analysis and queries – The depth of functionality and scope of support for advanced business analytics tool features are becoming comparable to full Business Intelligence (BI) suites and platforms. The progression of advanced features often begin with business analytics tools, before progressing to BI suites, applications and platforms.
- Business Analytics tools designed to improve data exploration, including visual discovery, grew the fastest of all tool categories, according to the BARC Research and Eckerson Group study: BI and Data Management in the Cloud: Issues and Trends. The combined research study found that adoption of business analytics doubled between 2013 and 2016. One in five organizations added analytical applications last year. The following is a graphic from the study:
- Additional factors that differentiate cutting-edge business analytics tools include extensive support for dashboard reporting (76%); ad-hoc analysis and exploration (57%); and dashboard authoring (55%). The same BARC Research and Eckerson Group study also found that respondents are most interested in adding advanced and predictive analytics (53%); operational planning and forecasting (44%); and strategic planning and simulation (44%). The following graphic provides an overview of the primary use cases of cloud BI in the respondent’s organization, taking into account their adoption of business analytics tools:
- Early adopters of cutting-edge business analytics tools are seeking to gain greater data insights that can improve their core businesses, with 50% adopting machine learning-based apps this year. Of those adopting machine learning-based business analytics tools, 46% are seeking greater competitive advantage, while 45% are looking for faster data analysis and speed of insight. Additionally, 44% are looking at how they can use machine learning to gain enhanced R&D capabilities that lead to next-generation products. These and many other insights are from a recent survey completed by MIT Technology Review Custom and Google Cloud, Machine Learning: The New Proving Ground for Competitive Advantage.
The List of Cutting-Edge Business Analytics Tools
The most cutting-edge business analytics tools are bridging the gap between business-led, descriptive analytics and predictive, contextual analytics that provide business users with advanced modeling capabilities. As a group, they illustrate how quickly business analytics tools are overlapping with traditional BI applications. The seven most cutting-edge business analytics tools are:
- Amazon QuickSight – Amazon Web Service’s (AWS) cloud-based business analytics service supports ad-hoc analytics, dashboards and visualizations, making it possible to connect with data sets quickly and generate results. QuickSight’s architecture includes the AWS Super-fast, Parallel, In-memory Calculation Engine (SPICE) that enables accurate connections with data so visualizations, dashboards and reports can be produced and published quickly. QuickSight has a free evaluation version worth checking out. You can find QuickSight here: https://quicksight.aws/.
- Attivio – Attivio has significantly refined its cognitive search and insight platform in the last three years, and offers a free trial on their website. Attivio excels at contextual intelligence, relying on a series of Wizards to guide users through data import, analysis and presentation of results. Attivio is one of the most advanced business analytics tools that can provide contextual intelligence from diverse data sets. The platform today includes support for machine learning algorithms, NLP and knowledge graphing. You can find the Attivio site here: https://www.attivio.com/.
- Clear Analytics – Built on Microsoft Excel, Clear Analytics offers advanced business analytics features including visualization, report sharing, publishing and report generation, all from a single application. Business users rate Clear Analytics as having excellent flexibility and ease in creating reports, dashboards and updating Key Performance Indicators (KPIs). Audit and compliance tracking are also designed into the application, making it possible to scale across larger organizations and create the data needed to pass audits. You can find the Clear Analytics site here, where the company offers a free trial: http://www.clearanalyticsbi.com/.
- Endor – A data discovery service that’s cpreloud-based and created using MIT-based research, Endor uses social physics to seek out and expand patterns in socially-derived data sets. By seeking out dynamic patterns and signals in social and human-derived data, Endor creates predictive data results that can be modified over time through additional queries and questions. It’s an exceptionally easy tool to use, as it supports natural language queries and doesn’t require large datasets to generate results. You can find the Endor site here: http://www.endor.com/.
- Google Charts – A comprehensive collection of charts and graphs that can be quickly customized and embedded in applications and websites, Google Charts excels at taking a wide variety of datasets and creating clear, concise graphics from them. Google Charts’ versatility is apparent based on its support of everything from line charts to complex hierarchical tree maps. Charts are rendered using HTML5/SVG technology to provide cross-browser compatibility (including VML for older IE versions) and cross-platform portability to iPhones, iPads and Android devices. Google Charts is free to use, and you can find their site here: https://developers.google.com/chart/.
- Microsoft Power BI – One of the easiest and most powerful business analytics tools to use, Microsoft Power BI provides a versatile base of features for completing the analysis, visualization and presentation of diverse analytics projects. Microsoft Power BI excels at data source import and integration; interactive visual exploration; and usability across all Internet-enabled devices, from laptops to smartphones. You can find the main Microsoft Power BI site here: https://powerbi.microsoft.com/en-us/, and Microsoft’s free version here: https://powerbi.microsoft.com/en-us/get-started/.
- Nutonian Eureqa – Nutonian can import data that isn’t specifically coded for use in Artificial Intelligence (AI) engines, and can also generate advanced analytics, predictive and prescriptive models. The company has nine patents today, and is working on more centered on how AI engines and supporting technologies can be made more accessible to business users. It’s possible to quickly get up and running with this tool and begin building models without having to hire a data scientist to get work done. You can find the Nutonian site here: https://www.nutonian.com/.
Business analytics tools are proliferating today, as are advanced technologies including machine learning, NLP and NLG. Every business analytics tools provider is designing greater usability and self-service, alleviating the need to have data scientists on staff to get advanced analysis and model building done. These seven cutting-edge business analytics tools reflect how successful software providers have been in simplifying complex analytics and BI workflows to increase adoption. All of them are succeeding in making business analytics more available across a broader base of business users than ever before.