Business analytics (BA) tools have reached an inflection point. This change is driven by the need to increase the depths of functionality tools deliver without a data scientist supporting them. Businesses are developing advanced technologies to meet this new need, including Natural Language Processing (NLP) and Hadoop.
Over 100 new business analytics tools have entered the market within the last 18 months. Defining which are the most cutting edge begins with a series of criteria. Once the criteria is created, you must progress through an assessment of each. These tools excel in dimensions of ease of use, intuitive navigation design and depth of integration points. Each has the potential to scale beyond their core functions such as data analysis. Business Analytical tools can provide deeper insight by adding support of advanced modeling.
- Gartner predicts that by 2020, more than 75% of large and midsize global organizations will deploy advanced analytics as part of a platform or data analytics applications. This increase will help improve present and future business decisions.
- State-of-the-art analytics tools are being developed to provide the most powerful data analytics features to business processes. By doing so, businesses will no longer need to hire hard-to-find data scientists.
- The 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 analysis tools is becoming defined by new applications that support data exploration via intuitive interfaces. These apps will have support for analysis workflows using something like an NLP.
- Providing business analysts the ability to “upgrade” advanced analytic models without the help of a data scientist is an innovative development. It will revolutionize how big data is handled as well as the progression of BA tools for years to come.
- These tools are enabling efficient collection, correlation and presentation of semi-structured data. In doing so, it makes it possible to find new patterns in real-time data sets to build new models.
What Defines A Cutting Edge Business Analytics Tool?
With hundreds of new tools introduced every year, defining which are the most cutting edge can be tricky. But it’s possible when you lay everything out in front of you. First, identify the most important needs of your users by using a series of criteria. Keep in mind that Business Analysts, managers, and line-of-business staff members are the most frequent users of these tools. They are typically the decision makers in proceeding with purchasing tools for the company. The following criteria was gather through conversations with key players at various businesses:
- Intuitive, easy-to-use interface that’s customizable by business analysts – Business analysts and other power users value certain features, like flexibility, in their software. For example, defining workflows, model creation and user interfaces are some of the features they value above others. The most cutting-edge business analytics tools are capable of guiding even non-technical users through the model creation process. They provide 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 among the crowd and one people choose often. However, there are many smaller, faster-moving companies than IBM that are breaking new ground today by using NLP. Amazon QuickSight, Attivio, Endor and Microsoft Power BI are examples of business analytics tools that are actively developing applications. They use NLP and Natural Language Generation (NLG) responses for queries. These advanced business analytics tools don’t require a data scientist to get them 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 tools build advanced analytics algorithms. They prompt users to see how they want data represented. Data analytics tools capable of generating contextualized insights are in high demand. They save time and generate knowledge which was previously unknown.
- Cutting-edge business analytics tools also can combine multiple sources of complex data, scaling from the transactional to the unstructured – Big data can scale from the transactional to the unstructured. During a recent conversation, one CIO remarked that over 60% of his company’s data is semi-structured and unstructured. He was looking for tools that allow flexibility to analyze structured, semi-structured and unstructured data. He needed to find tools that wouldn’t require an IT analyst or data scientist.
- The ability to test advanced statistical models iteratively using machine learning algorithms – Another criterion business analysts -and those who are a part of the decision making process- mention is the ability to define test parameters for analytics models. They said it was crucial to have machine learning-based algorithms seek optimal outcomes.This functionality is typically found in higher-end, enterprise-wide BI platforms. New tools are beginning to incorporate this functionality into 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 begin with business analytics tools, then 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 found that respondents were most interested in adding three features. The features they were most concerned about were : 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. It takes 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. 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 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
Cutting-edge business analytical tools are bridging the gap between business-led, descriptive analytics and predictive, contextual analytics. As a group, they illustrate how quickly business analytics tools are overlapping with traditional BI applications. Here are the seven most cutting-edge solutions to your big data needs:
- Amazon QuickSight – Amazon Web Service’s (AWS) cloud-based service supports ad-hoc analytics, dashboards and visualizations. These features make it possible to connect with data sets quickly and generate results. QuickSight’s architecture includes the AWS Super-fast, Parallel, and In-memory Calculation Engine (SPICE). These connections with data allow visualizations, dashboards and reports to be rapidly produced and published. 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. They’ve even begun offering 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. Because of this, it is one of the most advanced business analytics tools that provides contextual intelligence from diverse data sets. Attivio is truly one of the best solutions to understand your data. 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 a wide range of advanced business analytics features. These features include: visualization, report sharing, publishing and report generation. 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 designed into the application as well, making it possible to scale across larger organizations and create the data needed to pass audits. You can find the Clear Analytics site here and receive a free trial: http://www.clearanalyticsbi.com/.
- Endor – Endor is a data discovery service that’s cpreloud-based and created using MIT-based research. It uses social physics to seek out and expand patterns in socially-derived data sets. By seeking out dynamic patterns in social and human-derived data, Endor creates predictive data results. The results Endor produces can modify additional queries and questions over time. It’s an easy tool to use, and supports natural language queries. It also doesn’t require big data sets to generate results. You can find the Endor site here: http://www.endor.com/.
- Google Charts – Google Charts excels at taking a wide variety of data sets and creating clear, concise graphics from them. Google Charts’ versatility is apparent based on its support of functions like line charts and 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 diverse analytics projects. This tool is excellent at data source import and integration, interactive visual exploration and usability across all Internet-enabled devices. Not only does it offer a number of unique features, but it makes the process of finishing projects easier. 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. It can also generate advanced analytics, predictive and prescriptive models. The company has nine patents today, and is working on adding additional ones. They plan to have patents centered on how AI engines and supporting technologies can be more accessible to business users. It’s possible to quickly get things started with this tool to begin building models without hiring a data scientist. You can find the Nutonian site here: https://www.nutonian.com/.
Business analytics tools are proliferating today. So are advanced technologies including machine learning, NLP and NLG. Every business analytics tools provider is designing greater usability and self-service. They want to alleviate the need to have data scientists on staff to get advanced analysis and model building done. Taking steps to make these changes helps users find quick solutions and streamline decision making overall. 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.