DATA INTELLIGENCE

Turn the catalog into answers for IT, finance, and governance alike.

Data intelligence turns the Diskover catalog into dashboards, reports, heatmaps, and cost analysis. See what is growing, what has gone cold, what each team’s storage costs, and what changed since the last scan. Then act on the answer.

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Data intelligence in Diskover: storage capacity and storage cost by department, the hot and cold split, and the share of files not used in 6 months

WHO IT SERVES

Four teams, four questions,
one catalog.

Every team asks about storage in its own words. Each answer comes from the same catalog, so the numbers match from one team to the next.

IT and storage teams.

What is growing the fastest, which data has gone cold, and what can we delete?

Finance.

What does each department, project, or client cost us in storage?

Project and research leads.

How much space does each project use, and how fast is it growing?

Governance.

Which files are older than our retention policy, and who owns them?

ANALYTICS

Analytics built on the catalog.

Dashboard

A snapshot of every indexed system, or one volume: file and folder counts, hot and cold data, top file types, largest files and folders, and the files not used in the last 6 months.
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Smart Searches

Saved searches shared across the organization, grouped by any category, such as project, customer, or storage tier, with charts by count and size.
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Storage Space

Total, used, and available space for every indexed volume, bucket, or share, side by side. Spot the locations close to full before they become an emergency.
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Cost Analysis

Storage cost by category, such as tier, client, project, or age. Your team enters the cost per gigabyte for each system, and Diskover applies it to every file.
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User Analysis

Storage, cost, and file count by owner and by group, with each one’s share of the total. See who holds the most data, and start cleanup conversations with the right people.
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Tags

How many files and how much storage carry each tag, such as archive, keep, or legal hold. See the decisions your teams and rules have made, in one view.
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HEATMAP

See what changed between two scans.

The heatmap compares two scans of the same system, or two systems, such as on-premises storage and its cloud backup. Growth shows in red and reduction in green, sized by capacity or by file count, so the folders driving growth stand out before the next purchase.

Diskover heatmap comparing two scans of project folders, with growth in red and reduction in green, and a table of size changes per folder

SCHEDULED REPORTS

Reports that arrive on schedule.

Recurring questions deserve recurring answers. A scheduled report runs a saved query after each scan or on a set schedule, then emails the result as a CSV file or writes it as a Parquet file for your analytics tools.

  • For the storage team: the largest and oldest files on each tier, every week.
  • For finance: capacity and cost by department, every quarter.
  • For your lakehouse: the same metadata as Parquet, ready to query. Explore data lakes and lakehouses →

Every Monday, 7:00 AM

cold_by_tier.csv → emailed to storage-team

cold_by_tier.parquet → written to the lakehouse

BI TOOLS

Your storage numbers, in the BI tools you already use.

Storage data becomes more useful next to the rest of the business. Diskover sends catalog metadata where your analysts already work, so they can build storage dashboards in their own tools and join them with project, cost center, or sales data.

Through Snowflake.

Curated file metadata arrives as rows in your Snowflake account, so any BI tool connected to Snowflake can query it.
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As Parquet or CSV files.

Scheduled reports write Parquet for your lakehouse or email CSV after each scan, ready for any BI tool that reads them.
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Through the API.

The REST API and Python SDK feed storage data into your own scripts, pipelines, and dashboards, whenever you need it.
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One catalog, the same numbers in Diskover and in your BI dashboards.

AI CONNECTOR

Ask your storage a question.

The AI Connector answers plain-language questions from the same catalog, with your group permissions, and recommends a next step for a person to approve.

  • Which teams or projects are growing fastest, and on which systems?
  • Which project folders have not been modified in 12 months?
  • Show storage used by each department, largest first.
  • Tag files older than 2 years in the shared drives as archive candidates.
Explore the AI Connector

NEXT STEPS

From insight to action.

Clean up.

Tag duplicates, old and temporary files, then run cleanup by policy.
Explore orchestration

Tier.

Move cold data to lower-cost storage, and keep it searchable.
Explore data mobility

Report on it in BI.

Send catalog metadata to Snowflake or your lakehouse.
Explore data lakehouses

FAQ

Questions about data intelligence.

Data intelligence turns file metadata into answers: what you have, where it lives, who owns it, how fast it grows, and what it costs. Diskover builds it from one catalog of every file across your storage.
Your team enters a cost per gigabyte, globally or per volume or folder, and it can include hardware, cloud fees, power, support, and staff time. Diskover applies that rate to every file, so you see cost by tier, project, owner, or any category you define.
Yes. The heatmap compares two scans and shows growth in red and reduction in green, folder by folder.
Yes. A scheduled report runs a saved query after each scan or on a set schedule, and emails a CSV file or writes a Parquet file for your analytics tools.
No. Reports come from rich metadata, such as name, path, owner, and tags, plus enriched metadata from plugins. One option is the exception: to confirm exact duplicates, a plugin can read each file to compute a checksum. Diskover keeps only that code, never the content. That keeps analytics fast at petabyte scale.”

See it on your own data.

We’ll index a sample of your environment and show you
what’s recoverable against your current storage spend.

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