Digital.ai Analytics Lenses Use data to drive continuous improvement across the software lifecycle.

Improve decisions by leveraging purpose-built analytics solutions to instantly answer questions about what is happening, formulate hypotheses about why it is happening, and investigate.

What you get with an Analytics Lens

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Fast time to insight

Bring your data to life with a range of dashboards that present clear and compelling insights. An intuitive drag-and-drop interface makes it quick and easy to explore data using grids, graphs, charts, and maps.

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Data-driven decisions

Leverage robust analytical capabilities that include out-of-the-box metrics, dimensional hierarchies, and ad-hoc analysis. Improve decision making by diagnosing not only what is happening, but why.

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The right information at the right time

Unearth relevant insights wherever they may be with a data model that is source-agnostic and enterprise grade. Gain instant access to the information you need to make effective decisions.

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Quick time to value

Pre-built, intelligent connectors integrate with a wide range of applications. In addition to native integrations with Digital.ai solutions, integrations with third-party solutions include BMC, ServiceNow, Cisco AppDynamics, Atlassian Jira, Jenkins, and many others.

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Plan & Create Analytics Lens

Enable agile teams to use data-driven insights to improve development efficiency, prioritize the most important features, and deliver products with more value. Leaders can analyze work item status, team velocity, and sprint progress to improve development team performance and create a unified view across the product portfolio. The solution includes out-of-the-box integration with team and portfolio agile planning, product portfolio management (PPM) solutions, and others.

Plan and Create - Sprint Analysis

Sprint analysis

Monitor team issue resolution progress by tracking the time to resolve critical bugs, team workload balance, and efficiency trends between sprints.

Plan and Create - Project Backlog

Project backlog

Manage the status of backlog items by highlighting the age of items and and team progress towards delivering features that provide value.

Plan and Create - Program Increment

Program increment

Increase agile team velocity by setting performance goals, observing results across different features, and identifying ways to improve.

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Integrate & Verify Analytics Lens

Enable development and QA teams to use data driven insights to improve user experience through better code quality, higher testing effectiveness, and reduced defect leakage. Leaders can analyze code coverage, build & test automation, test cases, test execution/coverage and defects to spot and deep dive into systemic issues and trends. The solution includes out-of-the-box integration with common CI and quality tools, among others.

Integrate and Verify - Build Success

Build success

Raise the quality and reliability of software builds by analyzing success metrics, build failure reasons, build failures, and aborted builds.

Integrate and Verify - Test Automation

Test automation

Improve QA efficiency and effectiveness and identify opportunities to invest in greater test coverage and automation.

Integrate and Verify - Release Quality

Release quality

Monitor release quality metrics and fix quality issues with a birds eye view across testing, defects, and code quality.

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Release & Deploy Analytics Lens

Enable DevOps teams to use advanced analytics to gain data-driven insights to identify bottlenecks, improve release process efficiency using key metrics, and increase release reliability while reducing risk. This lens gathers data from across the entire end-to-end DevOps toolchain, including the release pipeline and integrated tools to deliver true impactful insights and flexible visualizations that provide value and improve outcomes.

Release and Deploy - Phase Analysis

Release phase analysis

Track the time spent across phases of the release process, locate steps that are unreliable or unpredictable, and identify critical bottlenecks reducing release frequency.

Release and Deploy - Task Execution

Task execution review

Breakdown the release process according to time spent in each task, identify opportunities to automate manual tasks, and monitor the number of successful releases over time.

Release and Deploy - Release Overview

Release overview

Gain a comprehensive summary of recent releases from a single view, highlighting task risk, schedule predictability, and the percentage of release failures.

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Operate & Monitor Analytics Lens

Help ITSM leaders to improve customer experience by driving continual service improvements while reducing the costs of incident, problem, change, and request management. IT Operations leaders can move beyond simple process KPIs to analyze structured and unstructured data from the systems landscape. The solution includes integrations with enterprise ITSM, Change Management, CMDB, and APM systems, among others.

Operate and Monitor - Application Change Impact

Application change impact

Quickly formulate and validate hypotheses for major incident root cause by correlating changes with downstream impact, including incidents and application performance metrics.

Operate and Monitor - Vendor Performance

Team & vendor performance

Encourage data-driven transparency among ITSM teams through carefully chosen KPIs that map to organizational objectives.​

Operate and Monitor - Major Incident Hotspot

Major incident hotspots

Take proactive action to prevent major incidents by identifying hotspots by location, application, configuration item or assignment group.

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Panoramic View

By bringing multiple Digital.ai Analytics Lenses together, leaders can get a panoramic view across the entire software lifecycle. This panoramic view provides the operational intelligence needed to proactively make data-driven decisions, set the right strategies, and measure progress. For example, an issue in one part of the software lifecycle (e.g., low release quality) has its root cause in another area (e.g., not following continuous integration best practices). To help teams explore these types of correlations, all Digital.ai Analytics Lenses have been designed to enable cross-domain analysis.

Product owner

Product owner

Comprehensive visibility across the software lifecycle that helps product owners find, analyze, and fix issues wherever they may be in planning, development, or operations.

Application Health

Application health

Make data-driven decisions based on composite application health and scores across performance and IT service metrics such as incidents, problems, changes, outages, downtime, user and business impact.

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DORA metrics

We are the only platform that can provide all four DORA metrics plus Availability, enabling DevOps teams to track and increase the performance of their software release processes, get critical features to customers faster, and improve system reliability and availability.

DORA Metrics

Deployment frequency

Track the number of deployments per application each week to monitor team performance against goals, trends, and any impacts due to issues.

DORA - Lead Time

Lead time for changes

Identify application releases experiencing long lead times, highlighting bottlenecks, and identifying opportunities to get customers the features they need more quickly.

DORA - MTTR

Time to restore service (MTTR)

Reduce system downtime by gaining an understanding of which applications are the slowest to recover after a service incident or outage.

DORA - Change Failure Rate

Change failure rate

Increase release reliability and frequency by identifying applications that are regularly changing that are resulting in the highest failure rates.

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Availability

Monitor and track system uptime over a period of time, highlighting any trends to address and individual applications experiencing regular unavailability.

Enterprise-size problems require enterprise-grade solutions

Purpose-built analytics solutions provide insights both within a single domain and a panoramic view that spans the entire software lifecycle. The Digital.ai Platform brings together software lifecycle orchestration targeted AI and software lifecycle orchestration solutions that improve software delivery efficiency, reliability, and business impact.

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