When companies misstep — by rolling out Cheeto-flavored chapstick, say, or lighter-shaped Bic perfume — they’ve usually strayed from their greatest strengths. (Hint: No one’s greatest strength is cheesy chapstick.)
Meanwhile, companies that lean into what they do best often grow, fast. Take Uber: Leadership knew the strength of their rideshare app’s vehicle-tracking and route optimization technologies, and they leveraged both to create the food-delivery app Uber Eats, now worth billions.
That kind of institutional self-knowledge often stems from business intelligence products and platforms — tools that transform internal data into strategic insights about what’s currently working for a company and what could work in the future.
The insights are sometimes abstract (i.e. yes, we should lean into our vehicle-tracking capabilities!) and sometimes grounded. Business intelligence for restaurants, for instance, helps pinpoint bottlenecks in kitchen workflows and highlight popular dishes.
Today’s crop of business intelligence products grew out of 1970s computer information systems, a.k.a. “decision support systems,” that relied heavily on Excel. In this era of big data, though, Excel no longer suffices for most enterprises. Besides the fact that it lacks sufficient power, most enterprise data — 85 percent of it, by one estimate — consists of unstructured information, like text, that isn’t very spreadsheet-friendly.
Consequently, modern business intelligence platforms have abandoned spreadsheets. They instead rely on new technologies like SQL databases, cloud platforms and machine-learning to help enterprises make more self-aware, evidence-based decisions. Some platforms create forecasting models; some mine existing data for insights; some create live visualizations. One even comes with a SmarterChild-like AI bot that chats with users about their data.
Here are 20 examples of business intelligence companies that are gleaning insights from internal data.
What it does: From hardware to software, this business analytics platform was designed for the food industry. Toast’s kitchen hardware can withstand hotter temperatures than conventional tablets. The software’s restaurant-specific analytics also help managers identify bottlenecks in kitchen workflows or, at the front of the house, track how diner volume fluctuates by day and season.
What it does: Tableau ensures that everyone in an enterprise can see essential patterns and correlations in enterprise data — without coding. Rather than technical data mining, the company’s signature desktop product emphasizes the human eye’s innate pattern-spotting ability. Hence the visualizations ranging from color-coded maps to live graphics that update in real time.
Location: Irvine, Calif.
What it does: Alteryx’s Gartner-honored platform aims to free up time for data analysts so they can do more data analysis. By many estimates, data prep eats up as much as 90 percent of data workers’ time. Alteryx’s platform streamlines the processes of data cleaning and blending, making both coding-optional. Meanwhile, the machine-learning-enabled interface allows for rigorous analysis, with collaboration-friendly tools for predictive and spatial modeling.
What it does: InsightSquared’s revenue intelligence software captures every detail of a company’s “ funnel” — the processes by which leads become sales. That requires synthesizing tons of data to attribute each dollar earned to particular marketing campaigns, sales strategies and individual reps. The platform produces live reports and dashboards that bridge communication gaps between sales and marketing departments.
What it does: Action IQ’s customer data platform powers personalized marketing campaigns for clients like Verizon and the New York Times. Its AI framework weaves data from social media, transactions and myriad other integrations into multidimensional consumer profiles. From there, marketers can use a simple drag-and-drop user interface to target audiences based on their web history and real-time behavior.
What it does: Information Builders’ scalable business intelligence platform, WebFOCUS, guides users through the stages of data processing, from prep to visualization and deployment. Its slick interface lets non-technical users create predictive models and parse Internet of Things sensor data. “Insight” mode offers a visual overview of enterprise data that can expose hidden patterns.
Location: Santa Cruz, Calif.
What it does: This business analytics platform eliminates the chore of data extraction by working directly with SQL databases. Its platform autonomously generates SQL code that leads to relevant insights and visualizations, like Sankey diagrams and treemaps. Users simply need to sketch out the metrics that matter most to their business in the interface’s proprietary data-modeling language, Looker ML.
Location: Palo Alto, Calif.
What it does: Spotfire, TIBCO’s AI-powered platform, simplifies data analysis. Its smart interface functions as a human-like assistant, recommending modeling approaches, highlighting trends and outliers and grasping the core meaning of naturally-phrased search queries. The platform swiftly parses real-time data streams, too, from Internet of Things devices and messaging services.
Location: West Chester, Pa.
What it does: Instead of software, this firm provides tech experts that help companies optimize their data practices with data science principles, custom dashboards and Hadoop warehousing. A certified partner of Tableau and IBM, WayPoint makes popular technology work for clients in highly regulated and specialized industries like healthcare and finance.
Location: San Francisco
What it does: GoodData’s clients can deliver real-time custom analytics to their users with embedded dashboards. The dashboards are outfitted with intuitive interfaces and machine-learning algorithms that constantly improve their predictive capacities, and have led to corporate partnerships. Companies working with customer service platform Zendesk, for example, can visually track their ticket volumes, response times and more via GoodData dashboards.
Location: Toronto, Ontario, Canada
What it does: Dundas’ reporting and analytics platform automatically adapts to each user, which means business analysts enjoy intuitive drag-and-drop functionality and developers have room to code. Users can further modify and style their experiences at will, uploading their own data and creating custom visualizations that incorporate filtering and conditional formatting.
Location: San Francisco
What it does: Segment has attracted clients like Instacart and Levis with its business intelligence platform. Users collect and warehouse data through Segment’s single all-purpose API. They can then apply more than 200 analytical tools, including a live debugging feature, assorted filters and marketing tools that let them target specific consumer personas. In keeping with the EU’s new privacy laws, Segment also allows for data erasure.
Location: Vienna, Va.
What it does: The open design of this business intelligence platform allows for a broad spectrum of analytical projects. Microstrategy integrates with Mapbox and ESRI, for instance, so users can create data-driven maps. The platform also provides a flexible foundation for machine-learning algorithms and links to Alexa and Google Home for verbal querying.
Location: Radnor, Pa.
What it does: Qlik’s platform unleashes AI on data, making even massive repositories of information feel manageable. The platform’s AI-powered Associative Engine can grasp interconnections between varied datasets and recommend directions and parameters for analysis. (It can also conduct routine analysis autonomously.) Users who prefer conversation to visualization can chat with the platform’s AI-fueled Insight Bot, a Wall-E-esque cartoon.
Location: Redwood City, Calif.
What it does: Alation’s business insight platform not only autonomously inventories and indexes data, it contextualizes it. During analysis, its machine learning algorithms suggest query tweaks and remind users of best practices. They can also learn and recommend typical usage patterns or surface metadata with clarifying glossaries.
Location: San Francisco
What it does: Birst specializes in networked business insights. That means that on their decentralized platform, the IT department owns the data, but individual users can still blend data into the enterprise’s overall data pool. Birst’s system reflects updates from both owners and users in real time, and offers AI-powered analytics primed to discover data-driven explanations for mystifying phenomena.
Location: San Jose, Calif.
What it does: Numerify’s suite of applications integrates enterprise data from various sources, tags it with relevant metadata and sifts through it all for insights. The company’s analytical tools stand out for sheer modernity: Numerify offers natural language processing algorithms and in-memory cubes, efficient alternatives to relational tables. The team overseeing the Numerify platform works around the clock, too, ensuring no more than 0.01 percent downtime.
Location: San Mateo, Calif.
What it does: Fractal Analytics’ AI-powered tools turn typically opaque data formats into business insights. Used in fields like retail and healthcare, the company’s tools can parse the tone of reviews and social media posts with sentiment analysis, or scan images and videos with computer vision. Their tools allows brands to track retail stock of their wares and health insurers to better calculate patient risk by analyzing call center transcripts.
Location: Campbell, Calif.
What it does: Designed with the life sciences in mind, Saama’s SaaS analytics platform streamlines pharmaceutical development. By ingesting and integrating varied data sets, it accelerates study design and execution, offering intelligence on optimal study locations, cohort structures and risk management strategies. The powerful platform also offers AI-powered forecasts of potential market share for new drugs.
Location: San Francisco
What it does: Instead of waiting to be told what consumer behavior to track, Heap tracks it all — from desktop clicks and mobile swipes to completed transactions. The platform stockpiles relevant data not only from client sites, but from an array of partner sites like Salesforce and Shopify. Users can mine the resulting stash without coding, flexibly categorizing customer interactions into Virtual Events.
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