Analyze the data storage sector for me

Screening Filters

1. market_cap: min $5B

• Purpose: Focus on established, scalable public companies.
• Rationale: The data storage sector includes many smaller, highly speculative names. A $5B minimum market cap filters for firms with enough scale, liquidity, and market relevance to represent the sector meaningfully, rather than micro-cap or niche players.

2. volume: min 1,000,000

• Purpose: Ensure the stocks are actively traded and liquid.
• Rationale: High daily volume is important for sector analysis because it helps exclude illiquid names that can distort sector trends. It also makes the screened stocks more practical to trade or compare.

3. themes: Big Data, Cloud Computing, The Internet of Things, Software as a Service, AI Beneficiary

• Purpose: Capture companies most exposed to the modern data infrastructure ecosystem.
• Rationale: “Data storage” is closely tied to cloud infrastructure, analytics, AI workloads, SaaS platforms, and connected-device data generation. These themes identify companies that are either direct storage enablers or strong beneficiaries of rising data creation and retention demand.

4. region: US

• Purpose: Limit the universe to U.S.-listed companies.
• Rationale: This keeps the results consistent and easier to compare using the same accounting, regulatory, and market structure. It also matches the most common investable universe for U.S. sector analysis.

5. revenue_ttm: min $1B

• Purpose: Screen for companies with meaningful trailing sales.
• Rationale: In a sector analysis, revenue is a useful way to avoid companies that are too early-stage or whose business models are still unproven. Data storage businesses often need scale to compete on infrastructure, software, and enterprise contracts, so this helps isolate credible sector leaders.

6. gross_margin: min 30%

• Purpose: Identify companies with solid unit economics.
• Rationale: Storage-related businesses can range from low-margin hardware models to higher-margin software/platform models. A 30% gross margin threshold filters for stronger business quality and helps emphasize firms that may have better pricing power, recurring revenue, or more efficient scaling.

7. free_cash_flow_ttm: min 0

• Purpose: Focus on companies that are at least cash-flow positive.
• Rationale: For a sector view, free cash flow positivity is a strong indicator of financial durability. It excludes names that may be growing but are still burning cash, which makes the final set more stable and better suited for analysis of established data storage businesses.

Why These Results Match:

• The combination of big market cap + strong revenue + positive cash flow targets mature, investable companies rather than speculative startups.
• The theme filters ensure the screen captures firms truly connected to data storage demand, including cloud, AI, Big Data, and IoT-driven data generation.
• Volume and U.S. listing improve liquidity and comparability, making the output more useful for sector-level review.
• Gross margin helps tilt the screen toward higher-quality businesses, which is especially important in a technology sub-sector where profitability can vary widely.

Overall, these filters are appropriate because they narrow the universe to large, liquid, financially healthier U.S. companies that are most likely to be involved in or benefit from the data storage ecosystem.