It's Probably Here... Somewhere

Discovery process

A third of all small-to-medium sized businesses still use documents and spreadsheets for expenses and timekeeping, incurring time and expense to ingest into financial software. Similarly, most organizations maintain separate contact lists in their sales CRM and marketing software, leading to overlapping data and missed opportunities. Perhaps as much as 75% of global GDP is generated by companies that still rely on paper-based processes.

The reality is that most organizations work within a fragmented data ecosystem: critical information is distributed between spreadsheets, databases, shared drives, emails, and third-party platforms. Not having structured access or data interoperability makes data difficult to use, easily outdated, and vulnerable to breaches and accidental exfiltration.

Belay works with organizations to perform comprehensive data discovery - identifying, organizing, and connecting information so that a complete data ecosystem can be seen in one place, with all its relationships, patterns, and vulnerabilities.

Real-World Data Intake

For organizations that rely on external or analog processes, or within challenging data acquisition environments, data is often inaccessible because it exists on paper, in voicemails, on PostIts, or in archives spread across external services and physical media. For some organizations, data may not exist at all because of the difficulty of capturing it, structuring it and maintaining it.

Belay excels at difficult data, creating custom data acquisition workflows that work in high- and low-fidelity environments. Data science begins not in the office but on the asembly line, on the construction site, and in the healt clinic. Understanding data flows at the source means that solving data problems also solves real-world, human problems.

The Belay Approach

1 Inventory Identify all data assets across the organization - structured and unstructured, on-premises or in the cloud.
2 Acquire Create new workflows to bring uncollected or unstructured data into the organization.
3 Correct Fix data discrepancies resulting from multiple unsynchronized collection methods. Apply common data standards and protocols.
4 Structure Transform messy, unstructured data into clean, usable formats. Make information searchable, consistent, and ready for analysis.
5 Connect Link data from distributed systems into a unified view of assets and relationships. Break down silos and reveal areas of perishability or duplication.
6 Visualize Explore relationships, flows, and dependencies through a bird's-eye view of the organization's data footprint.
7 Protect Highlight vulnerabilities, redundancies, and blind spots. Ensure protection of sensitive assets.

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