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プラットフォーム · データ&アナリティクス

ひとつのデータファブリック。ひとつの真実の源。 Every view derived from it.

Market, alternative and operational data land on one ordered, time-aware event stream. The warehouse, research, reports and the Observatory all read from the same record, and every answer Ask Ada gives cites the decision ledger.

Source of truth

One canonical stream. No second set of books.

Positions, trades, prices and factor exposures land on a single ordered log. Warehouse tables are materialized views of it; streams are the same log, live; research features are the same log, windowed. Every dashboard, backtest and filing draft answers the same question with the same numbers.

It is the same data plane Adaptic runs its proprietary fund on, with its own capital.

The usual stack

Extracts, reconciliations, a daily miracle.

OMS to a reconciliation engine, administrator to a warehouse, warehouse to a BI tool, and a feature store nobody trusts. Three dashboards, three numbers, and an afternoon deciding which one is right.

Adaptic, by design

One stream every view derives from.

One canonical event stream that every feed, model and dashboard derives from. Live by default, point-in-time correct by construction, and able to reproduce an old view on demand.

Data fabric

Clean enough for models, risk and audit.

Market, alternative and operational data normalized into one time-aware fabric, with one schema across the firm.

  • Unified warehouseA warehouse-native model of positions, trades, prices, factors and reference data. One schema, firmwide.
  • Live streamsEvent streams for orders, fills, prices and risk updates, so dashboards and alerts never wait for an overnight batch.
  • Versioned and time-awarePoint-in-time correctness by construction. A view rebuilt years later reproduces what the firm saw at the time.
  • Data catalogEvery field documented, owned and lineage-tracked, so an analyst can trust what they query without asking around.
リネージの仕組み

ソース記録から再現可能な答えへ。 to reproducible answer.

五つのステージが、単一の数値を、到達した瞬間から届出に現れる瞬間まで運びます — そのいずれもが追跡可能であり、いずれもがリプレイ可能です。

  • 01 · Source captureEvery inbound message, whether a vendor tick, a broker drop or an administrator file, is hashed, timestamped and written to an insert-only staging log before any parser touches it.
  • 02 · Canonical modellingTyped, schema-validated events are appended to the canonical stream, each pointing back to its source record.
  • 03 · Feature derivationFeatures are computed as ordered transforms over the canonical log, each carrying the exact code version that produced it.
  • 04 · Point-in-time replayRe-run a prior-period report with that period’s data, code and mandate, and get the same answer.
  • 05 · Governance and accessPersonal, material non-public and restricted fields are tagged at ingest and enforced in the query engine itself, not at the dashboard.
Observatory

Every trade explains itself.

The Observatory reads the record and renders it. Trace any outcome from portfolio to name to factor and back, or ask Ada in plain language; every answer cites the ledger.

Ask Ada

Why was the single-name order refused this morning?

Pre-trade refused it: the order would have taken the name to 7.3% against the mandate’s 7.0% cap. It was recorded and returned to the agent; no human action was required.

Cites ledger row #18342 · Mandate v3 · §4.2

Illustrative sample response

  • Portfolio lensPosture, limits and headroom: the distance to every threshold the mandate sets.
  • Name lensThesis, position and lineage, including the clause that authorized the size.
  • Factor lensRates, dollar, oil, volatility, growth, credit and liquidity, traced to the exposure behind a move.

The Observatory does not write, approve or release capital. A report or filing Ada drafts needs a named approver before it goes anywhere.

Research and reporting

Built on the record, not bolted on.

Research and reporting live alongside the data, reading the same versioned record the kernel and the Observatory read.

Research

  • Feature storeEngineered factors and alternative-data features, versioned and reproducible, feeding research notebooks and live models alike.
  • NotebooksA notebook workspace with the warehouse connected and access enforced: no CSV exports, no orphaned notebooks on laptops.
  • BacktestingReplay, slippage and stress as a standing gate, run against versioned, point-in-time data.
  • Model evaluationRobustness and drift measured continuously against reproducible inputs.

Reporting

  • Report draftsStatements, risk and compliance views and board packs, drafted from the ledger and exported to PDF or XLSX.
  • AttributionFactor-level attribution and exposure reporting, drilling down to the underlying positions.
  • Compliance viewsSurveillance and exception reporting drawn from the same canonical record.
  • ApprovalA material statement waits for a named approver before it is sent.
データソース

機関投資家チームが用いるソースに、あらかじめ配線済み。 investment teams use.

Adaptic は、投資チームが実際に用いる参照、価格、マイクロストラクチャー、オルタナティブデータ、ファンドアドミン、ウェアハウス、ストリーミングのソースに接続するよう設計されており、それ以外のすべてにはブリング・ユア・オウン・キーの経路を備えます。

  • platformData.sources.categories.referencePricingBloomberg · Refinitiv / LSEG · FactSet · S&P Capital IQ · ICE · Morningstar
  • Market dataNasdaq TotalView · Cboe · NYSE · Databento · Polygon.io · Kaiko
  • platformData.sources.categories.alternativeDataYipitData · M Science · RavenPack · Quandl / Nasdaq Data Link
  • Fund accounting and administrationSS&C GlobeOp · Citco · SEI · Northern Trust
  • Warehouse targetsSnowflake · Databricks · BigQuery · Redshift
  • platformData.sources.categories.streamingBiKafka · Redpanda · Tableau · Power BI

ベンダー名は、本システムが対応するよう設計された統合連携のターゲットを示すものであり、ここに掲載されていることは、推奨または既存の商業的関係を意味するものではございません。

データ責任者からの質問

CDO が最初に尋ねること。 asks first.

はい。Adaptic は正規スキーマをウェアハウスネイティブにモデリングするため、置き換えるのではなく、お客様がすでに保有するウェアハウスの上で稼働するよう設計されています。既存の契約、ガバナンス、リージョンは、お客様のものであり続けます。

コーポレートアクションと修正再表示は、上書きされることなく、新しいイベントとして正規ログに追記されます。ポイントインタイム・リプレイは、修正再表示の前にブックが在ったとおりに正確に再構成するため、過去のレポートは再現可能であり続けます。

はい。フィーチャーストアとノートブック環境は、本番エンジンが読み取るのと同じバージョン管理されたデータに接続するため、リサーチ用ノートブックと稼働中のモデルは同一の特徴量を供給されるよう設計されています — 並行するパイプラインも、リサーチと本番との間の照合もございません。

Streaming views read the log directly rather than waiting for the warehouse, so a dashboard reflects the record as events land instead of after a nightly batch.

DBT と Airflow は、お客様がなお組み立てなければならないウェアハウスの上で変換をオーケストレーションします。Adaptic は、正規スキーマ、リネージ、フィーチャーストア、ガバナンスを一つのシステムとして提供するため、モデリング層とオーケストレーション層は、配線して繋ぐのではなく、設計に組み込まれています。

正規ログと導出ビューは、管轄区域ごとにパーティション分割し、クラウドのリージョンにピン留めできます。Adaptic は、リージョンにピン留めされた完全に分離されたコントロールプレーンを、リージョン間レプリケーションをデフォルトで無効化したうえでデプロイできます。

Six-week shadow pilot

Stop migrating data. Start reading it.

In a six-week shadow pilot we load a sample extract from your current stack into a read-only Adaptic warehouse, with no capital at risk, so you can see your data on one record.