Motio Products Make Your Business Intelligence Platform Better

Our passion is to take great BI Tools and improve upon them, helping users soar in what they can achieve in analytics.

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MotioCI

The comprehensive solution for your Cognos Analytics. Through automation, teams can improve analytics asset management, streamline deployments, recover deleted reports in seconds, and execute regression testing, resulting in turbocharged analytics development. All this while optimizing performance, cost, and risk management through a holistic asset management approach that ensures your business’s vitality.

Soterre

Gain automation and oversight of the continuous delivery process for a trusted Qlik Sense, Qlik SaaS, or Power BI experience.

MotioPI

In addition to recovering lost or damaged Cognos Framework models, Motio PI Professional gives you the ability to ensure correct security roles, batch validate Cognos reports and objects, enjoy rich search and replace to eliminate tedious time sinks, and perform a world of automations to more efficiently manage your Cognos assets.

ReportCard

Keep Cognos performance optimized with a proactive solution that assesses where and when your platform is lagging.

MotioCAP

Let Motio connect your IBM Cognos environment to your security infrastructure with our fully supported Custom Authentication Provider or SAML solutions.

Persona IQ

Use Persona IQ® to seamlessly migrate your Cognos content and configuration from one authentication namespace to another—with no loss of CAMIDs.

Digital Hive

Bring all the data, systems, and environments that matter most to you within a single, intuitive user experience.

Gitoqlok

Premium support for the easy-to-use web plugin that integrates Qlik Sense with your Git provider, creating traceability and the impact of changes.

QSDA Pro

QSDA Pro supports DevOps for BI engineers, automating Qlik app validation and offering actionable insights. Seamlessly test directly within Qlik when using QSDA Pro with Gitoqlok, and when combined with Soterre, QSDA Pro ensures efficient, error-free Qlik implementations for streamlined development workflows.

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As the BI space evolves, organizations must take into account the bottom line of amassing analytics assets.
The more assets you have, the greater the cost to your business. There are the hard costs of keeping redundant assets, i.e., cloud or server capacity. Accumulating multiple versions of the same visualization not only takes up space, but BI vendors are moving to capacity pricing. Companies now pay more if you have more dashboards, apps, and reports. Earlier, we spoke about dependencies. Keeping redundant assets increases the number of dependencies and therefore the complexity. This comes with a price tag.
The implications of asset failures differ, and the business’s repercussions can be minimal or drastic.
Different industries have distinct regulatory requirements to meet. The impact may be minimal if a report for an end-of-year close has a mislabeled column that the sales or marketing department uses, On the other hand, if a healthcare or financial report does not meet the needs of a HIPPA or SOX compliance report, the company and its C-level suite may face severe penalties and reputational damage. Another example is a report that is shared externally. During an update of the report specs, the low-level security was incorrectly applied, which caused people to have access to personal information.
The complexity of assets influences their likelihood of encountering issues.
The last thing a business wants is for a report or app to fail at a crucial moment. If you know the report is complex and has a lot of dependencies, then the probability of failure caused by IT changes is high. That means a change request should be taken into account. Dependency graphs become important. If it is a straightforward sales report that tells notes by salesperson by account, any changes made do not have the same impact on the report, even if it fails. BI operations should treat these reports differently during change.
Not all reports and dashboards fail the same; some reports may lag, definitions might change, or data accuracy and relevance could wane. Understanding these variations aids in better risk anticipation.

Marketing uses several reports for its campaigns – standard analytic assets often delivered through marketing tools. Finance has very complex reports converted from Excel to BI tools while incorporating different consolidation rules. The marketing reports have a different failure mode than the financial reports. They, therefore, need to be managed differently.

It’s time for the company’s monthly business review. The marketing department proceeds to report on leads acquired per salesperson. Unfortunately, half the team has left the organization, and the data fails to load accurately. While this is an inconvenience for the marketing group, it isn’t detrimental to the business. However, a failure in financial reporting for a human resource consulting firm with 1000s contractors that contains critical and complex calculations about sickness, fees, hours, etc, has major implications and needs to be managed differently.

Acknowledging that assets transition through distinct phases allows for effective management decisions at each stage. As new visualizations are released, the information leads to broad use and adoption.
Think back to the start of the pandemic. COVID dashboards were quickly put together and released to the business, showing pertinent information: how the virus spreads, demographics affected the business and risks, etc. At the time, it was relevant and served its purpose. As we moved past the pandemic, COVID-specific information became obsolete, and reporting is integrated into regular HR reporting.
Reports and dashboards are crafted to deliver valuable insights for stakeholders. Over time, though, the worth of assets changes.
When a company opens its first store in a certain area, there are many elements it needs to understand – other stores in the area, traffic patterns, pricing of products, what products to sell, etc. Once the store is operational for some time, specifics are not as important, and it can adopt the standard reporting. The tailor-made analytic assets become irrelevant and no longer add value to the store manager.