PHPMem v2.0.1
Version
1.6.45
Uptime
15 days 19 hours 16 minutes 58 seconds
Memory
Total
512MB
Used
9,38MB (1.83%)
Free
502,62MB
Keys
Current
11 436
Total (since start)
35 066
Evictions
0
Reclaimed
738
Expired Unfetched
0
Evicted Unfetched
0
Connections
Current
7 / 1 024 max
Total
178 850
Rejected
0
llm:fe04934177a375e4357da1cc886fa48e7af45fb61d2b377498ac70948cba29c0
Edit
{
"action": "final",
"content": "## Dataset Overview\n\nThis dataset captures **the largest venture capital funding deals in the United States during 2023**. It serves as a market intelligence snapshot, documenting where significant venture capital flowed during a pivotal year for startup financing.\n\n## What a Single Row Represents\n\nEach row represents **one major venture funding deal** announced in 2023. Specifically, a row captures:\n\n- **The company** that received funding\n- **The funding amount** raised in that round\n- **Lead investors** backing the deal\n- **The company's valuation** at the time of funding\n- **The industry sector** the company operates in\n- **The date** the deal was reported\n\nThe dataset contains **171 such deals**, representing a curated selection of the highest-value funding rounds rather than an exhaustive list of all venture transactions. This filtering by deal size makes it particularly useful for understanding where the largest capital commitments occurred and which sectors attracted the most significant investor attention.\n\n## Primary Use Cases\n\nBased on the dataset's structure, it serves audiences such as:\n\n- **Venture capital investors and analysts** tracking market trends and competitive positioning\n- **Startup founders and CFOs** benchmarking valuations and timing fundraising efforts\n- **Corporate development teams** identifying acquisition targets or partnership opportunities\n- **Market researchers** analyzing sector-level funding patterns and investor behavior\n\nThe data is observational in nature—it documents deals that occurred rather than tracking ongoing operational metrics—making it ideal for strategic analysis, competitive intelligence, and market trend identification rather than operational decision-making."
}