Data Inventory Project
Our two-week Data Landscape Inventory is designed to give you a clear picture of your current data environment. By focusing on practical insights and straightforward recommendations, we’ll help you plan and prioritise your data initiatives with confidence. We specialise in data and are passionate about helping organisations increase their data literacy and confidence when making decisions about data.
What Problems Does a Data Landscape Inventory Resolve?
Ambiguity
Teams often make decisions based on incomplete or outdated data, leading to misaligned priorities and costly mistakes. Our inventory provides a single source of truth to eliminate confusion and ensure everyone is on the same page.
Hidden Costs
Vendor and database costs can be opaque, making it hard to identify inefficiencies. We uncover size, usage, and connectivity insights, helping you reduce costs by consolidating and retiring unused systems.
Project Risks
Lack of data clarity puts critical initiatives like migrations, AI readiness, and application transitions at risk. We identify key dependencies, risks like naming inconsistencies or broken links, and ensure smooth execution. Some example of projects that have a high risk profile if data literacy isn’t at a high level are:
Data Migration - we recommend a business-driven approach where technical and business experts can agree on design decisions using a shared data dictionary which operates at both a logical and a physical level
Data Ingestion Readiness for AI - knowing where your key data resides and how to extract to a specific format needed by your AI solution of choice is key to optimising the accuracy of your AI’s expertise level
Application Transition - the full impact of an application transition must be understood from the outset rather than a heads-down (and often in the sand) approach. Whether enhancing an existing application, replacing or decommissioning altogether or transitioning from on-premise to the cloud, the data flow interdependencies between integrated applications and access requirements to databases needs to be clearly understood so that migration strategies are included to manage risks
What You Can Expect
Project Planning & Discovery
We start by cataloguing your applications and databases to build a clear picture of where your data resides. This keeps everyone on the same page and significantly reduces the risk of conflicting priorities or rework.
Risk Management & Dependencies
Our next step is to map how different systems interact, revealing any bottlenecks or risk points before they become serious problems. By spotting these early, you can prevent unexpected setbacks and keep your modernisation initiatives moving forward.
Project Health & Quality Control
We keep an eye on data consistency, highlighting issues such as naming inconsistencies or referential integrity risks. This proactive approach helps maintain a smooth project flow and minimises last-minute surprises.
Cost Management & Optimisation
Using server and database analytics, we locate inefficiencies, highlight legacy systems, and uncover opportunities for consolidation. This approach helps you optimise vendor relationships and free up budget for the projects that truly drive value.
Communication and Collaboration
Our reports combine technical data with contextual data to facilitate clearer communication between your teams. This provides clear data lineage from physical data models to the Applications and Business contexts that depend on data and the data flows between Applications.
Pricing
We provide this service for a fixed price of NZ$15,000 + GST. Additional work can be delivered as agreed.
How It Works
Preparation
Scoping Session: We facilitate a free, no-obligation session to understand your objectives, database environment, and define clear project deliverables.
Metadata Extraction: Your technical team runs provided queries against your MSSQL Servers to generate metadata-only CSV extracts.
Contextual Questionnaire: You'll complete our Excel template to provide essential business context that helps us analyse your data environment from multiple perspectives.
Week 1: Discovery & Initial Findings
Kick-off & Resource Gathering: We'll review all existing documentation and validate the metadata collected during preparation.
Data Mapping & Risk Analysis: Analyse your data sources, pinpoint dependencies, and flag any pressing quality issues.
Week 2: Detailed Insights & Action Plan
Quality Assessment: Identify inconsistencies and areas for immediate improvement.
Cost & Efficiency Review: Highlight where you can streamline resources to save on budget.
Recommendations: Deliver a concise summary of findings and an outline of clear next steps.
We conduct all sessions virtually.
Post Delivery
We'll schedule a follow-up call two weeks after delivery to gather your feedback and discuss potential next steps.
Results
By the end of our two-week engagement, you’ll have a clear, comprehensive inventory of your entire data ecosystem and a focused report outlining any critical dependencies or potential risks.
We’ll also provide actionable feedback on naming conventions and data consistency, helping you improve data quality across your organisation.
Finally, you’ll receive insights into cost and resource optimisation opportunities so you can streamline processes and reduce unnecessary spend. We provide all deliverables in PDF format.
Next step: fill out the form to contact us and find out more.