Most of the calls we get do not start with a technology name. They start with a problem: reports that do not agree, a BI bill that keeps climbing, a pile of documents nobody can search, a spreadsheet someone has to update by hand every Monday, or a system the vendor is about to stop supporting. These are five problems clients bring to DIS, in the words our clients use, and how we fix each one.
Our reports never match
An IT director pulls a revenue number from the ERP. A sales director pulls what looks like the same number from the CRM. They do not match, and nobody can say why without a week of tracing spreadsheets. This happens when the systems of record, ERP, CRM, accounting, property management, were never meant to agree with one another, and every team has quietly built its own version of the truth.
We fix it by building one trusted view across the systems that hold the data today, not by ripping them out. That means connecting to systems like NetSuite, Sage Intacct, QuickBooks, JD Edwards, Microsoft Dynamics 365, Oracle EBS, Epicor, Acumatica, Salesforce, HubSpot, Zoho, and, for real estate and property management, Yardi, Entrata, RealPage, MRI, and AppFolio, and bringing them into a single, governed model that every team reports from. Our case study on data warehouse modernization covers one version of this: diverse data sources unified into a single, holistic view, with a 50% reduction in data processing time across critical pipelines.
Our BI tools cost too much
A lot of organizations are running several BI tools at once, one per department, each with its own license, its own maintenance, and its own training. Nobody set out to build it that way. It happened one renewal at a time.
Where it makes sense, we help clients move reporting onto Microsoft's own analytics stack, Power BI, Microsoft Fabric, and Azure Databricks, so dashboards, pipelines, and governance live under one roof instead of several. This is a move off tools like Domo, Tableau, Qlik, MicroStrategy, Oracle BI, Cognos, Business Objects, SSRS, Crystal Reports, Informatica, and SSIS, not a comment on how well any of them work for someone else. It is about what one team can reasonably own and license going forward. See how we approach this kind of work on our services page.
We're not ready for AI, our data is a mess
Leadership teams know they should be doing something with AI but are not sure their data can support it. Usually the data is not missing, it is just scattered: a folder of contracts nobody indexed, three data lakes that grew up separately, a pilot project that stalled because the underlying pipeline was never finished.
Before any model gets built, we unify the data silos, make documents and PDFs something a system can actually search and reason over, and fix the projects that were started but never delivered. The tools we use for this are Microsoft Fabric, Azure Databricks, Microsoft Purview for governance, Microsoft Foundry to build and ground the AI itself, and Azure Document Intelligence to pull structured data out of documents and PDFs. Our AI predictive maintenance case study is what this looks like once the data is ready: a 30% reduction in equipment downtime for a manufacturing client.
We still do it by hand
Data entry that gets typed in twice. Approvals that move through email and a shared inbox. A report someone rebuilds from scratch every week because nobody automated the last mile. None of this is a data problem exactly, it is a workflow problem sitting on top of the data.
We automate it with Power Automate for the workflows, Power Apps for the low-code front ends, Fabric and Databricks apps where the automation needs to sit closer to the data platform itself, and Microsoft Copilot Studio where a conversational layer helps a team get an answer without opening a report at all. Our HR onboarding automation case study shows the kind of result this work produces: a 30% reduction in total onboarding time, from offer to first day.
Our legacy systems are reaching end of support
Some systems keep running long after the vendor has stopped actively supporting them, and every year that passes makes the eventual move harder, not easier. SAP ECC is one example, and the same conversation comes up around Oracle EBS, JD Edwards, IBM AS/400, Dynamics GP and AX, Teradata, Netezza, and on-premises SQL Server or Oracle.
Our answer is the same in each case: move the platform to Microsoft Azure, and put the data it holds to work rather than leaving it locked inside a system that is winding down. That is Azure migration in the fullest sense, infrastructure, databases, and the reporting layer on top, not just a lift and shift. Our cloud migration case study is a secure move to Azure for a financial institution, with zero data loss and no security incidents.
Where to start
These five show up in almost every conversation we have, sometimes one at a time, often two or three together. If one of them sounds like your week, our services page is a good place to see how we structure the work, or you can tell us directly what is not working.