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rmancinas 7e65fc81d5 Add legacy database structural reference for non-Windows machines

docs/LEGACY_DATABASES.md documents all three source Access databases
(every table, column, type, and known data-quality quirk) generated
from a live read of the real files, so no Windows/Access driver is
needed to understand their structure going forward.

New migration/ tooling: catalog_schema.py connects to the real files
and walks every table (including excluded scratch tables);
render_catalog_md.py renders that into the doc's appendix. Raw output
checked in at migration/catalog.json so the doc can be regenerated
without touching Access again.

2026-07-22 01:41:53 -07:00

61 KiB

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Legacy Database Reference

A complete structural reference for the four MS Access source databases this platform migrates from, written so a machine without Windows and without access to the original files can still understand exactly what data exists, how it's shaped, and what's already known to be broken or excluded.

Why this file exists

The source data lives in Microsoft Access (.accdb/.mdb) files. That format can only be read directly via the Microsoft Access Database Engine ODBC driver, which is Windows-only — there is no equivalent driver for Linux/macOS, and pyodbc on those platforms has nothing to connect to. In practice this means:

Anyone working from a non-Windows machine (or without the original files at hand) cannot open these databases themselves.
This document is the substitute: it was generated by actually connecting to the real files on a Windows machine and reading every table's structure, so it can be trusted as an accurate snapshot rather than a guess.
For the data itself (not just structure), work from the staged output instead — see Working with this without Windows below.

Source of truth / how to regenerate: migration/catalog_schema.py connects to all three real database files and writes a full JSON catalog; migration/render_catalog_md.py renders that JSON into the appendix at the bottom of this file. Re-run both (on Windows, with the Access ODBC driver installed) any time the source .accdb/.mdb files change:

cd migration
python catalog_schema.py --output catalog.json
python render_catalog_md.py catalog.json --output appendix.md
# then paste appendix.md content below the --- marker at the bottom of this file

The four files at a glance

File	Format	Size	Tables	Purpose
`UTILITIES.accdb`	Access 2007+	~538 MB	52 (37 real, 15 scratch)	Property/utility-service management: customers, properties, per-service billing (water/electric/gas/cable/trust/property-tax), cash ledgers
`SEGUROS 16.mdb`	Access 2003 (Jet)	~30 MB	0 real	Empty linked front-end shell. All actual data lives in the `_be` file below — this file just holds forms/reports/queries pointing at it.
`SEGUROS 16_be.mdb`	Access 2003 (Jet)	~882 MB	64 (49 real, 15 scratch)	Insurance brokerage backend: customers, one table per line of business (fire, multi-risk/home, auto ×7 variants, commercial, driver's-license), claims, beneficiaries, adjusters
`SCOTHIA.mdb`	Access 2003 (Jet)	~3 MB	7 (4 real, 3 scratch)	The office's own Scotiabank checking-account register ("chequera") — not customer data, the company's operating bank book

None of these files have any primary keys, foreign keys, or other referential-integrity constraints defined at the database level — every relationship described below is inferred from column-naming conventions, not enforced by the source system. Treat every "this column references that table" statement here as an educated inference to validate during migration, not a guarantee.

How the three real databases relate to each other

The same people are customers of both the utilities and insurance business lines, and the two systems cross-reference each other in a few specific places:

UTILITIES.accdb: DATGRAL.[NUM id] ↔ SEGUROS 16_be.mdb: DATGRAL.[NUM UTIL] — the insurance customer table has a literal column pointing at the corresponding utilities customer's ID. This is the primary join key for building a unified customer record, and is almost certainly what the old PHP app's customer_mapping table was reverse-engineered from.
SEGUROS 16_be.mdb: UTILSEG (1,582 rows, 3 columns) — looks like a dedicated utilities↔insurance customer cross-reference table, likely redundant with the NUM UTIL column above but worth reconciling against it rather than assuming either is complete on its own.
SCOTHIA.mdb doesn't reference customers at all — it's the company's own bank book. It cross-references business lines instead, via TABLA RAMODOS (a "ramo"/line-of-business lookup that bank transactions presumably classify against through their CONCEPTO/TIPO free-text fields — there's no formal foreign key, so this mapping would need to be inferred from the text, not joined directly).
Within UTILITIES.accdb, COBRO3 (181 rows) has the exact same column shape as DATGRAL (1,172 rows) and looks like a filtered snapshot rather than a distinct entity — needs a diff before assuming it's redundant.
Within SEGUROS 16_be.mdb, one flat table exists per insurance line of business — INCENDIO (fire), MULT (multi-risk/home), M EMPR (commercial property), seven auto-policy variants (TABLA AUTOS, TABLA AUTOS AMPL, TABLA AUTOS AMPL R, TABLA AUTOS LIMIT, TABLA AUTOS LIMIT R, TABLA AUTOS RC R, MCA2), and LICENCIAS (driver's-license insurance) — these all share the same repeated-column pattern (policy #, coverage dates, 4 hardcoded payment installments, premium breakdown, liquidation status) and are meant to unify into one policies table with a type discriminator in the target schema, not stay as separate tables.

Known data-quality issues and extraction quirks

These were discovered by actually connecting to the files, not by inspection — anyone re-running extraction should expect to hit the same issues:

cursor.columns() UTF-16 decode bug. Reading column metadata (not data) via pyodbc's cursor.columns() call throws 'utf-16-le' codec can't decode bytes... on a subset of tables whose column names contain certain accented/special characters (confirmed on PROPANO, FALTANTES AGUA, TIT, and others — see the appendix, tables with no access_type shown hit this). Workaround: read column names from cursor.description after a plain SELECT * instead, which doesn't hit the same code path. Implemented in migration/extract.py::read_table. The cost is losing the nice Access type name (VARCHAR(255), DOUBLE, etc.) for those specific tables — the appendix falls back to showing the pandas-inferred dtype for them instead.
One corrupted record in MULT. A single row in SEGUROS 16_be.mdb: MULT is marked deleted at the Jet/ACE storage level but still enumerated by the driver — trying to read it throws HY109 Record is deleted. A plain fetchall() aborts the entire table on this error. Workaround: fetch rows one at a time in a try/except, skip and log the bad row, keep going. Recovers 763 of 764 rows. Confirmed the cursor correctly advances past the bad row rather than looping forever before trusting this for a full run. Implemented in migration/extract.py::read_table.
No real primary keys anywhere. Every ID-like column (NUM id, NUMid, NUMER ID, IDISEG, IDIUT, etc.) is a plain DOUBLE or INTEGER field with no uniqueness constraint enforced by the database. Duplicates are possible and should be checked for, not assumed absent.
IDs stored as DOUBLE, not INTEGER. Most legacy numeric ID columns are typed DOUBLE(53) even though every real value is a whole number — a legacy-of-Access-defaults quirk, not a meaningful design choice. Watch for floating-point representation issues when comparing/joining these values (e.g. 369.0 vs 369) during migration.
Column names are free-form, including spaces, colons, and inconsistent casing (NUM id, NUMid, NUMER ID, TRUST NUM:, A�O1 — that last one is a mis-decoded AÑO1, "year" in Spanish). migration/extract.py::sanitize_column_name normalizes these to safe identifiers for staging, while preserving the original name separately for traceability.
Near-duplicate snapshot tables. Several groups of tables in UTILITIES.accdb appear to be repeated exports/snapshots of the same underlying data across different periods or programs, not genuinely distinct datasets: the EFECTIVO / EFECTIVO FM3 / EFECTIVO_BACKUP / CHEQUE FM3 cash-ledger group, and the FEE ANUAL / datos2 / fee15 / billing recurring-billing group. These need a reconciliation/diff pass before deciding a union or de-dupe rule — don't assume a straight union is correct.

Table exclusion rationale

Tables excluded from migration (see migration/config.py for the exact per-source exclude lists) fall into three categories:

Confirmed empty (0 rows). Nothing is lost by skipping these — mostly named like obvious scratch/working tables (BANCO EDITOR, Errores de pegado, TABLE1, PARA BILLING*, FALTANTES *, TELEFONOS FECHAS, TRUSTHFEE, and the ID TABLA/TABLA LIQUIDA * group in the insurance file).
Mail-merge document templates, not data — the * MENS/*MENSAJE tables in SEGUROS 16_be.mdb (AMPL MENS, IN MENS, LIC MENS, MCA2 MENS, ME MENS, MF MENS, RC MENSAJE, RC R MENS) store letter/certificate templates as blobs. These get reimplemented as real PDF templates in the new app, not migrated as rows.
Materialized Access query results, not source-of-truth data — TODOSJC, TODOS, vigenta casa y auto unicos in the insurance file look like saved report output. If the report itself is still needed, it should be rebuilt as a real query against the new schema, not migrated as a frozen snapshot.

A TIT table appears in both UTILITIES.accdb and SEGUROS 16_be.mdb with 1 row each and column names matching Access's default "Contacts" template (FirstName, LastName, Address, City...) — almost certainly leftover template residue from database creation, not real data. Excluded from both.

Working with this without Windows

If you're on a non-Windows machine and need the actual data, not just the structure documented here:

The real extraction has to happen on a Windows machine with the Access ODBC driver (migration/load_staging.py) — there's no way around that for the raw .accdb/.mdb files themselves.
That script's output — either Parquet files (--output-dir, portable, no database needed) or a live MySQL staging load (--database-url) — is what every other machine should work from. Parquet in particular is fully cross-platform and needs nothing but pandas/pyarrow to read.
This document tells you what to expect in that staged output (which tables, which columns, what's already known to be messy) without needing to touch the original Access files at all.

See ../PLAN.md for the full target data model these tables migrate into, and ../RESUME.md for overall project state.

Appendix: full table catalog

Generated by migration/catalog_schema.py + migration/render_catalog_md.py. Regenerate after any change to the source files.

UTILITIES.accdb

52 tables total — 37 included in migration, 15 excluded (scratch/template/report tables).

`AGUA EVALUA`

Rows: 1 | Columns: 2

Column	Type	Nullable
`RUTAS`	VARCHAR(50)	no
`PERIODO`	VARCHAR(50)	no

`CHEQUE FM3`

Rows: 157 | Columns: 9

Column	Type	Nullable
`CL`	DOUBLE(53)	no
`FECHA`	DATETIME(19)	no
`FEE`	DOUBLE(53)	no
`TAX`	DOUBLE(53)	no
`MULTA`	DOUBLE(53)	no
`MONEDAS`	VARCHAR(50)	yes
`CONEPTO`	VARCHAR(100)	yes
`NUM CHEQUE`	DOUBLE(53)	no
`FOLIO`	COUNTER(10)	no

`CLAVES`

Rows: 8 | Columns: 4

Column	Type	Nullable
`BANCO`	VARCHAR(10)	no
`MANT`	VARCHAR(15)	yes
`PRZN`	VARCHAR(15)	yes
`ZFED T`	VARCHAR(15)	yes

`COBRO3`

Rows: 181 | Columns: 25

Column	Type	Nullable
`NUM id`	DOUBLE(53)	no
`NOMBRE`	VARCHAR(255)	yes
`DIRECCION`	VARCHAR(255)	yes
`COLONIA`	VARCHAR(255)	yes
`CIUDAD`	VARCHAR(255)	yes
`ESTADO`	VARCHAR(255)	yes
`PAIS`	VARCHAR(255)	yes
`LABEL`	VARCHAR(255)	yes
`TELUSA`	VARCHAR(255)	yes
`FAX`	VARCHAR(15)	yes
`OBSERVACIONES`	VARCHAR(255)	yes
`CODIGO`	VARCHAR(50)	yes
`TIPO`	DOUBLE(53)	yes
`CLIENTE TIPO`	VARCHAR(50)	yes
`FECHA NACIMIENTO`	DATETIME(19)	yes
`ESTADO DE CUENTA EN`	BIT(1)	no
`CONTROL FM3`	BIT(1)	no
`EMAIL`	VARCHAR(50)	yes
`CLIENTE DESDE`	DATETIME(19)	yes
`STATUS`	BIT(1)	no
`FEE`	DOUBLE(53)	no
`IDIUT`	DOUBLE(53)	no
`CEL`	VARCHAR(50)	yes
`ID SEG`	DOUBLE(53)	no
`ID FM`	DOUBLE(53)	no

`DATGRAL`

Rows: 1172 | Columns: 25

Column	Type	Nullable
`NUM id`	DOUBLE(53)	no
`NOMBRE`	VARCHAR(255)	yes
`DIRECCION`	VARCHAR(255)	yes
`COLONIA`	VARCHAR(255)	yes
`CIUDAD`	VARCHAR(255)	yes
`ESTADO`	VARCHAR(255)	yes
`PAIS`	VARCHAR(255)	yes
`LABEL`	VARCHAR(255)	yes
`TELUSA`	VARCHAR(255)	yes
`FAX`	VARCHAR(15)	yes
`OBSERVACIONES`	VARCHAR(255)	yes
`CODIGO`	VARCHAR(50)	yes
`TIPO`	DOUBLE(53)	yes
`CLIENTE TIPO`	VARCHAR(50)	yes
`FECHA NACIMIENTO`	DATETIME(19)	yes
`ESTADO DE CUENTA EN`	BIT(1)	no
`CONTROL FM3`	BIT(1)	no
`EMAIL`	VARCHAR(50)	yes
`CLIENTE DESDE`	DATETIME(19)	yes
`STATUS`	BIT(1)	no
`FEE`	DOUBLE(53)	yes
`IDIUT`	DOUBLE(53)	yes
`CEL`	VARCHAR(50)	yes
`ID SEG`	DOUBLE(53)	yes
`ID FM`	DOUBLE(53)	yes

`DATMEX`

Rows: 1520 | Columns: 56

Column	Type	Nullable
`NUMER ID`	DOUBLE(53)	no
`CASA`	DOUBLE(53)	no
`DIRECCION`	VARCHAR(255)	yes
`TELEFONO`	VARCHAR(50)	yes
`TELEFONO2`	VARCHAR(50)	yes
`TELEFONO3`	VARCHAR(50)	yes
`FV`	DOUBLE(53)	yes
`FV2`	DOUBLE(53)	yes
`FV3`	DOUBLE(53)	yes
`MANZANA`	VARCHAR(12)	yes
`LOTE`	VARCHAR(12)	yes
`AGUA`	DOUBLE(53)	yes
`DIAGUA`	DOUBLE(53)	yes
`GAS`	VARCHAR(12)	yes
`GAS VENCE`	DOUBLE(53)	yes
`ZONA`	VARCHAR(50)	yes
`CHECK`	VARCHAR(1)	yes
`CLAVE`	VARCHAR(50)	yes
`RUTA`	VARCHAR(50)	yes
`RUTA2`	VARCHAR(50)	yes
`RUTA3`	VARCHAR(50)	yes
`MEDIDOR`	VARCHAR(50)	yes
`MEDIDOR2`	VARCHAR(50)	yes
`MEDIDOR3`	VARCHAR(50)	yes
`LUZ TIPO`	VARCHAR(50)	yes
`BFEE`	DOUBLE(53)	yes
`CONSES`	VARCHAR(50)	yes
`BANCO`	VARCHAR(30)	yes
`VENCE1`	DATETIME(19)	yes
`VENCE2`	DATETIME(19)	yes
`MANT`	VARCHAR(15)	yes
`MANT$`	DOUBLE(53)	yes
`CIA CABLE`	VARCHAR(255)	yes
`DIA CABLE`	DOUBLE(53)	yes
`CABLE num`	VARCHAR(255)	yes
`PRZN`	VARCHAR(15)	yes
`PREDIAL`	DOUBLE(53)	yes
`ZFED`	DOUBLE(53)	yes
`FIANZA`	VARCHAR(50)	yes
`ZFED T`	VARCHAR(15)	yes
`TRUST NUM`	VARCHAR(50)	yes
`RPU`	DOUBLE(53)	yes
`RPU2`	DOUBLE(53)	yes
`RPU3`	DOUBLE(53)	yes
`TASA`	DOUBLE(53)	yes
`CABLE/SKY`	BIT(1)	no
`SERVICES`	LONGCHAR(1073741823)	yes
`ALARM SYSTEM`	VARCHAR(50)	yes
`TITULAR SERV`	BIT(1)	no
`VIGENTE`	BIT(1)	no
`ILUZ`	LONGBINARY(1073741823)	yes
`IAGUA`	LONGBINARY(1073741823)	yes
`IPREDIAL`	LONGBINARY(1073741823)	yes
`ITEL`	LONGBINARY(1073741823)	yes
`DOC 1`	LONGBINARY(1073741823)	yes
`DOC 2`	LONGBINARY(1073741823)	yes

`DATOS FUTUROS`

Rows: 0 | Columns: 7

Column	Type	Nullable
`NUMid`	DOUBLE(53)	—
`DATE`	DATETIME(19)	—
`REFER`	DOUBLE(53)	—
`PERIOD`	VARCHAR(255)	—
`TYPE OF TRX`	VARCHAR(255)	—
`CHARGECREDIT`	DOUBLE(53)	—
`CHEQUE`	VARCHAR(15)	—

`DIRECCION`

Rows: 0 | Columns: 4

Column	Type	Nullable
`ID`	INTEGER(10)	—
`HOME 1:`	VARCHAR(50)	—
`HOME 2:`	VARCHAR(50)	—
`HOME 3:`	VARCHAR(50)	—

`DIRECCIONAWEB`

Rows: 1520 | Columns: 2

Column	Type	Nullable
`ID`	DOUBLE(53)	no
`ADDRESS`	VARCHAR(50)	yes

`EFECTIVO`

Rows: 13697 | Columns: 8

Column	Type	Nullable
`CL`	SMALLINT(5)	no
`FECHA`	DATETIME(19)	yes
`MONTO`	CURRENCY(19)	yes
`MONEDAS`	VARCHAR(255)	yes
`CONEPTO`	VARCHAR(255)	yes
`F DEPOSITO`	DATETIME(19)	yes
`FOLIO`	COUNTER(10)	no
`ELABORO`	VARCHAR(255)	yes

`EFECTIVO FM3`

Rows: 627 | Columns: 9

Column	Type	Nullable
`CL`	DOUBLE(53)	no
`FECHA`	DATETIME(19)	no
`FEE`	DOUBLE(53)	yes
`TAX`	DOUBLE(53)	yes
`MULTA`	DOUBLE(53)	yes
`MONEDAS`	VARCHAR(50)	yes
`CONEPTO`	VARCHAR(100)	yes
`F DEPOSITO`	DATETIME(19)	yes
`FOLIO`	COUNTER(10)	no

`EFECTIVO_BACKUP`

Rows: 12387 | Columns: 8

Column	Type	Nullable
`CL`	DOUBLE(53)	no
`FECHA`	DATETIME(19)	yes
`MONTO`	DOUBLE(53)	yes
`MONEDAS`	VARCHAR(50)	yes
`CONEPTO`	VARCHAR(100)	yes
`F DEPOSITO`	DATETIME(19)	yes
`FOLIO`	COUNTER(10)	no
`ELABORO`	VARCHAR(50)	yes

`FECHAIF`

Rows: 1 | Columns: 2

Column	Type	Nullable
`FECHA INICIAL`	DATETIME(19)	no
`FECHA FINAL`	DATETIME(19)	no

`FECHAS`

Rows: 1 | Columns: 2

Column	Type	Nullable
`FECHA 1`	DATETIME(19)	no
`FECHA 2`	DATETIME(19)	no

`FEE ANUAL`

Rows: 1082 | Columns: 11

Column	Type	Nullable
`NUMid`	DOUBLE(53)	no
`DATE`	DATETIME(19)	no
`REFER`	VARCHAR(50)	yes
`PERIOD`	VARCHAR(255)	no
`TYPE OF TRX`	VARCHAR(255)	no
`CHARGECREDIT`	DOUBLE(53)	yes
`CHEQUE`	VARCHAR(15)	yes
`CAP`	DATETIME(19)	no
`per`	VARCHAR(50)	yes
`CONT`	COUNTER(10)	no
`NOPAGO`	BIT(1)	no

`IVA 2015`

Rows: 911 | Columns: 8

Column	Type	Nullable
`NUM id`	DOUBLE(53)	no
`CASA`	DOUBLE(53)	no
`NOMBRE`	VARCHAR(255)	yes
`DIRECCION`	VARCHAR(255)	yes
`FEE`	DOUBLE(53)	no
`VALORU`	DOUBLE(53)	no
`VALIVA`	DOUBLE(53)	no
`RECIBO`	COUNTER(10)	no

`LUZ EVALUA`

Rows: 1 | Columns: 2

Column	Type	Nullable
`RUTAS`	VARCHAR(50)	no
`PERIODO`	VARCHAR(50)	no

`LUZSCAN`

Rows: 0 | Columns: 5

Column	Type	Nullable
`ID`	DOUBLE(53)	—
`CASA`	DOUBLE(53)	—
`NOMBRE`	VARCHAR(50)	—
`RPUS`	VARCHAR(50)	—
`SALDO`	DOUBLE(53)	—

`MAIL`

Rows: 84 | Columns: 1

Column	Type	Nullable
`CLIENTE`	DOUBLE(53)	no

`PARAPER`

Rows: 0 | Columns: 1

Column	Type	Nullable
`per1`	VARCHAR(50)	—

`PROFILE`

Rows: 1520 | Columns: 14

Column	Type	Nullable
`NUMERID`	DOUBLE(53)	no
`CASA`	DOUBLE(53)	no
`DIRECCION`	VARCHAR(255)	yes
`PHONE1`	INTEGER(10)	no
`PHONEN`	VARCHAR(50)	yes
`WATER1`	INTEGER(10)	no
`GAS1`	INTEGER(10)	no
`FEDERALZONE`	INTEGER(10)	no
`PROPERTYTAXES`	INTEGER(10)	no
`ELECTRIC`	INTEGER(10)	no
`TRUST`	INTEGER(10)	no
`BANK`	VARCHAR(50)	yes
`CABLE/SKY`	BIT(1)	no
`SERVICES`	LONGCHAR(1073741823)	yes

`PROPANO`

Rows: 0 | Columns: 24

Column	Type	Nullable
`NUMid`	(inferred: object)	—
`NOMBRE`	(inferred: object)	—
`DIRECCION`	(inferred: object)	—
`COLONIA`	(inferred: object)	—
`CIUDAD`	(inferred: object)	—
`ESTADO`	(inferred: object)	—
`PAIS`	(inferred: object)	—
`CODIGO`	(inferred: object)	—
`EMAIL`	(inferred: object)	—
`TELUSA`	(inferred: object)	—
`FAX`	(inferred: object)	—
`DATE`	(inferred: object)	—
`REFER`	(inferred: object)	—
`PERIOD`	(inferred: object)	—
`TYPEOFTRX`	(inferred: object)	—
`CHARGECREDIT`	(inferred: object)	—
`MENSAJE`	(inferred: object)	—
`fdecreacion`	(inferred: object)	—
`PASSWD`	(inferred: object)	—
`CLIENTEDESDE`	(inferred: object)	—
`TIPODECAMBIO`	(inferred: object)	—
`TIPO`	(inferred: object)	—
`DIRECCIONMEX`	(inferred: object)	—
`NOPAGO`	(inferred: object)	—

`RECIBONOCLIENT`

Rows: 1 | Columns: 4

Column	Type	Nullable
`NOMBRE CLIENTE`	VARCHAR(50)	no
`CONCEPTO`	VARCHAR(200)	no
`CANTIDAD`	DOUBLE(53)	no
`MONEDAS`	VARCHAR(50)	no

`RPUN`

Rows: 0 | Columns: 4

Column	Type	Nullable
`NUMER ID`	INTEGER(10)	—
`NOMBRE`	VARCHAR(50)	—
`RPU1`	INTEGER(10)	—
`CH/CRED`	DOUBLE(53)	—

`SHCP 5`

Rows: 0 | Columns: 12

Column	Type	Nullable
`ID`	INTEGER(10)	—
`RFC`	VARCHAR(50)	—
`CURP`	VARCHAR(50)	—
`MES INICIO`	VARCHAR(50)	—
`AÑO INICIO`	VARCHAR(50)	—
`MES FINAL`	VARCHAR(50)	—
`AÑO FINAL`	VARCHAR(50)	—
`TOTAL DE DERECHOS`	DOUBLE(53)	—
`PARTE ACTUALIZADA`	DOUBLE(53)	—
`RECARGOS`	DOUBLE(53)	—
`MULTA`	DOUBLE(53)	—
`AJUSTE`	DOUBLE(53)	—

`TEL EVALUA`

Rows: 1 | Columns: 2

Column	Type	Nullable
`MES PAGO`	VARCHAR(50)	no
`FVT1`	DOUBLE(53)	no

`TELEF`

Rows: 0 | Columns: 4

Column	Type	Nullable
`ID`	DOUBLE(53)	—
`NOMBRE`	VARCHAR(50)	—
`TELE`	VARCHAR(50)	—
`SALDO`	DOUBLE(53)	—

`TIPO CAMBIO`

Rows: 1 | Columns: 3

Column	Type	Nullable
`TIPO DE CAMBIO`	(inferred: float64)	no
`MENSAJE`	(inferred: object)	no
`MENSAJE2`	(inferred: object)	yes

`TIPO HIST`

Rows: 2301 | Columns: 3

Column	Type	Nullable
`TIPO DE CAMBIO`	DOUBLE(53)	no
`DATE`	DATETIME(19)	no
`HOUR`	DATETIME(19)	no

`TRUSTVENCE`

Rows: 549 | Columns: 6

Column	Type	Nullable
`NUMER ID`	DOUBLE(53)	no
`BANCO`	VARCHAR(30)	no
`BFEE`	DOUBLE(53)	yes
`VENCE1`	DATETIME(19)	yes
`VENCE2`	DATETIME(19)	yes
`TRUST NUM`	VARCHAR(50)	yes

`TYPE OF TRX`

Rows: 79 | Columns: 2

Column	Type	Nullable
`TYPE OF TRX`	VARCHAR(50)	no
`ESPAÑOL`	VARCHAR(50)	yes

`datos2`

Rows: 16000 | Columns: 12

Column	Type	Nullable
`NUMid`	DOUBLE(53)	no
`DATE`	DATETIME(19)	yes
`REFER`	VARCHAR(50)	yes
`PERIOD`	VARCHAR(255)	yes
`TYPE OF TRX`	VARCHAR(255)	yes
`CHARGECREDIT`	DOUBLE(53)	yes
`CHEQUE`	VARCHAR(15)	yes
`CAP`	DATETIME(19)	no
`per`	VARCHAR(50)	yes
`CONT`	COUNTER(10)	no
`NOPAGO`	BIT(1)	no
`DUE DATE`	VARCHAR(50)	yes

`datosfreak`

Rows: 15981 | Columns: 26

Column	Type	Nullable
`NUMid`	(inferred: float64)	no
`NOMBRE`	(inferred: object)	yes
`DIRECCION`	(inferred: object)	yes
`COLONIA`	(inferred: object)	yes
`CIUDAD`	(inferred: object)	yes
`ESTADO`	(inferred: object)	yes
`PAIS`	(inferred: object)	yes
`CODIGO`	(inferred: object)	yes
`EMAIL`	(inferred: object)	yes
`TELUSA`	(inferred: object)	yes
`FAX`	(inferred: object)	yes
`CEL`	(inferred: object)	yes
`DATE`	(inferred: datetime64[ns])	yes
`REFER`	(inferred: object)	yes
`PERIOD`	(inferred: object)	yes
`TYPEOFTRX`	(inferred: object)	yes
`CHARGECREDIT`	(inferred: float64)	yes
`MENSAJE`	(inferred: object)	no
`fdecreacion`	(inferred: datetime64[ns])	no
`PASSWD`	(inferred: object)	no
`CLIENTEDESDE`	(inferred: datetime64[ns])	yes
`TIPODECAMBIO`	(inferred: float64)	no
`TIPO`	(inferred: float64)	yes
`DIRECCIONMEX`	(inferred: object)	yes
`NOPAGO`	(inferred: bool)	no
`FEE`	(inferred: float64)	yes

`datosfreak2`

Rows: 1520 | Columns: 2

Column	Type	Nullable
`NUMid`	(inferred: float64)	no
`DIRECCIONMEX`	(inferred: object)	yes

`fee15`

Rows: 1030 | Columns: 11

Column	Type	Nullable
`NUMid`	DOUBLE(53)	no
`DATE`	DATETIME(19)	no
`REFER`	VARCHAR(50)	yes
`PERIOD`	VARCHAR(255)	no
`TYPE OF TRX`	VARCHAR(255)	no
`CHARGECREDIT`	DOUBLE(53)	no
`CHEQUE`	VARCHAR(15)	no
`CAP`	DATETIME(19)	no
`per`	VARCHAR(50)	yes
`CONT`	COUNTER(10)	no
`NOPAGO`	BIT(1)	no

`pagos email`

Rows: 20 | Columns: 24

Column	Type	Nullable
`NUMid`	(inferred: float64)	no
`NOMBRE`	(inferred: object)	no
`DIRECCION`	(inferred: object)	yes
`COLONIA`	(inferred: object)	yes
`CIUDAD`	(inferred: object)	yes
`ESTADO`	(inferred: object)	yes
`PAIS`	(inferred: object)	yes
`CODIGO`	(inferred: object)	yes
`EMAIL`	(inferred: object)	yes
`TELUSA`	(inferred: object)	yes
`FAX`	(inferred: object)	yes
`DATE`	(inferred: datetime64[ns])	no
`REFER`	(inferred: object)	no
`PERIOD`	(inferred: object)	yes
`TYPEOFTRX`	(inferred: object)	no
`CHARGECREDIT`	(inferred: float64)	no
`MENSAJE`	(inferred: object)	no
`fdecreacion`	(inferred: datetime64[ns])	no
`PASSWD`	(inferred: object)	no
`CLIENTEDESDE`	(inferred: datetime64[ns])	yes
`TIPODECAMBIO`	(inferred: float64)	no
`TIPO`	(inferred: float64)	yes
`DIRECCIONMEX`	(inferred: object)	yes
`NOPAGO`	(inferred: bool)	no

`pagos todos`

Rows: 20 | Columns: 24

Column	Type	Nullable
`NUMid`	(inferred: float64)	no
`NOMBRE`	(inferred: object)	no
`DIRECCION`	(inferred: object)	yes
`COLONIA`	(inferred: object)	yes
`CIUDAD`	(inferred: object)	yes
`ESTADO`	(inferred: object)	yes
`PAIS`	(inferred: object)	yes
`CODIGO`	(inferred: object)	yes
`EMAIL`	(inferred: object)	yes
`TELUSA`	(inferred: object)	yes
`FAX`	(inferred: object)	yes
`DATE`	(inferred: datetime64[ns])	no
`REFER`	(inferred: object)	no
`PERIOD`	(inferred: object)	yes
`TYPEOFTRX`	(inferred: object)	no
`CHARGECREDIT`	(inferred: float64)	no
`MENSAJE`	(inferred: object)	no
`fdecreacion`	(inferred: datetime64[ns])	no
`PASSWD`	(inferred: object)	no
`CLIENTEDESDE`	(inferred: datetime64[ns])	yes
`TIPODECAMBIO`	(inferred: float64)	no
`TIPO`	(inferred: float64)	yes
`DIRECCIONMEX`	(inferred: object)	yes
`NOPAGO`	(inferred: bool)	no

Excluded tables

Table	Rows
`BANCO EDITOR`	0
`Errores de pegado`	1
`FALTANTES AGUA`	0
`FALTANTES TEL`	0
`LUZ TODOS`	0
`PARA BILLING SIN`	0
`PARA BILLING1`	0
`PARA BILLING2`	0
`PARA EDO`	0
`TABLE1`	13
`TELEFONOS FECHAS`	0
`TIT`	1
`TRUSTHFEE`	0
`billing`	0
`faltantes luz`	0

SEGUROS 16_be.mdb

64 tables total — 41 included in migration, 23 excluded (scratch/template/report tables).

`AJUSTA`

Rows: 3 | Columns: 1

Column	Type	Nullable
`AJUS`	VARCHAR(50)	no

`AJUSTADORES`

Rows: 9 | Columns: 6

Column	Type	Nullable
`ORDEN`	DOUBLE(53)	yes
`COMP`	VARCHAR(50)	yes
`CIUDAD`	VARCHAR(50)	yes
`NOMBRE`	VARCHAR(60)	yes
`TEL`	VARCHAR(50)	yes
`BEEPER`	VARCHAR(50)	yes

`AJUSTADORESATLAS`

Rows: 8 | Columns: 6

Column	Type	Nullable
`ORDEN`	DOUBLE(53)	no
`COMP`	VARCHAR(50)	no
`CIUDAD`	VARCHAR(50)	no
`NOMBRE`	VARCHAR(60)	no
`TEL`	VARCHAR(50)	yes
`BEEPER`	VARCHAR(50)	yes

`ATLAS`

Rows: 2 | Columns: 3

Column	Type	Nullable
`SEGURO`	VARCHAR(50)	no
`PNET`	DOUBLE(53)	no
`DPOLI`	DOUBLE(53)	no

`BENEF`

Rows: 768 | Columns: 5

Column	Type	Nullable
`BPOLIZA`	VARCHAR(255)	no
`BNOMBRE`	VARCHAR(255)	yes
`BDIRECCION`	VARCHAR(255)	yes
`BTEL`	VARCHAR(255)	yes
`BEMAIL`	VARCHAR(255)	yes

`COMENTARIOS`

Rows: 1 | Columns: 6

Column	Type	Nullable
`NUM`	COUNTER(10)	no
`EN`	VARCHAR(50)	no
`QUE`	VARCHAR(50)	no
`COMENTARIOS`	LONGCHAR(1073741823)	no
`FECHA`	DATETIME(19)	no
`OK`	BIT(1)	no

`COMPAN`

Rows: 4 | Columns: 1

Column	Type	Nullable
`COMPAÑIA`	VARCHAR(50)	no

`CONTACTS`

Rows: 3 | Columns: 26

Column	Type	Nullable
`ID`	COUNTER(10)	no
`COMPAÑIA`	VARCHAR(50)	no
`CARGO`	VARCHAR(50)	yes
`DEPARTAMENTO`	VARCHAR(50)	yes
`TITULO`	VARCHAR(50)	yes
`NOMBRES`	VARCHAR(50)	yes
`APELLIDOS`	VARCHAR(50)	yes
`CALLE Y NUM`	VARCHAR(50)	yes
`CIUDAD`	VARCHAR(50)	yes
`ESTADO`	VARCHAR(4)	yes
`CP`	VARCHAR(50)	yes
`REGION`	VARCHAR(50)	yes
`PAIS`	VARCHAR(50)	yes
`TEL TRABAJO1`	VARCHAR(30)	yes
`EXT1`	VARCHAR(20)	yes
`TEL TRABAJO2`	VARCHAR(30)	yes
`EXT2`	VARCHAR(20)	yes
`Tel Casa`	VARCHAR(30)	yes
`Celular`	VARCHAR(30)	yes
`Bipper`	VARCHAR(30)	yes
`Fax1`	VARCHAR(30)	yes
`Fax2`	VARCHAR(30)	yes
`Tel Emerg`	VARCHAR(30)	yes
`Email`	VARCHAR(50)	yes
`Cumpleaños`	DATETIME(19)	yes
`Notas`	LONGCHAR(1073741823)	yes

`DATGRAL`

Rows: 1070 | Columns: 25

Column	Type	Nullable
`NUM id`	(inferred: float64)	no
`NUM UTIL`	(inferred: float64)	yes
`NOMBRE`	(inferred: object)	yes
`DIRECCION 1`	(inferred: object)	yes
`DIRECCION 2`	(inferred: object)	yes
`CIUDAD`	(inferred: object)	yes
`ESTADO`	(inferred: object)	yes
`CODIGO`	(inferred: object)	yes
`PAIS`	(inferred: object)	yes
`TELUSA`	(inferred: object)	yes
`FAX`	(inferred: object)	yes
`TELEMERGENCIA`	(inferred: object)	yes
`CALLE Y NO`	(inferred: object)	yes
`COL`	(inferred: object)	yes
`CIUD`	(inferred: object)	yes
`EDO`	(inferred: object)	yes
`TEL`	(inferred: object)	yes
`EmailAddress`	(inferred: object)	yes
`FECHA NACIMIENTO`	(inferred: datetime64[ns])	yes
`OBSERVACIONES`	(inferred: object)	yes
`IDISEG`	(inferred: float64)	yes
`NUM FM`	(inferred: float64)	yes
`NO_IDENTIFICACION`	(inferred: object)	yes
`EXPIRA_IDENTIFICACION`	(inferred: datetime64[ns])	yes
`TIPO_IDENTIFICACION`	(inferred: object)	yes

`DATOS`

Rows: 2 | Columns: 50

Column	Type	Nullable
`POLIZA`	(inferred: int64)	no
`IDCLIENTE`	(inferred: float64)	no
`TIPO`	(inferred: object)	yes
`FECHA SINIESTRO`	(inferred: object)	yes
`DESCRIPCION`	(inferred: object)	yes
`FECHA REPORTADO`	(inferred: object)	yes
`FORMA`	(inferred: object)	yes
`COPIA DE POLIZA`	(inferred: bool)	no
`POLIZA LIQUIDADA`	(inferred: bool)	no
`DAÑOS VECINOS`	(inferred: bool)	no
`FECHA LIQUIDACION`	(inferred: object)	yes
`COMPAÑIA`	(inferred: object)	yes
`DESDE`	(inferred: object)	yes
`HASTA`	(inferred: object)	yes
`SERVICIO ADICONAL`	(inferred: bool)	no
`COMENTARIOS PROCEDE`	(inferred: object)	yes
`PROCEDE`	(inferred: bool)	no
`AJUSTADOR`	(inferred: object)	yes
`FECHA T AJUSTADOR`	(inferred: object)	yes
`FECHA V AJUSTADOR`	(inferred: object)	yes
`FECHA CONVENIO`	(inferred: object)	yes
`CARTA RECLAMACION`	(inferred: bool)	no
`CERTIFICADO M P`	(inferred: bool)	no
`NUM M P`	(inferred: int64)	no
`FECHA M P`	(inferred: object)	yes
`CERT BOMBEROS`	(inferred: bool)	no
`NUM BOMBEROS`	(inferred: float64)	no
`FECHA BOMBEROS`	(inferred: object)	yes
`CERT POLICIA FED`	(inferred: bool)	no
`NUM POLICIA FED`	(inferred: float64)	no
`FECHA POLICIA FED`	(inferred: object)	yes
`FINIQUITO`	(inferred: bool)	no
`NUM FINIQUITO`	(inferred: float64)	no
`FECHA FINIQUITO`	(inferred: object)	yes
`LESIONADOS`	(inferred: bool)	no
`DOCUMETO(S) ADIC`	(inferred: object)	yes
`DECLARACION ACCIDENTE`	(inferred: object)	yes
`CANTIDAD RECLAMADA`	(inferred: int64)	no
`CANTIDAD PACTADA`	(inferred: int64)	no
`FECHA CHEQUE`	(inferred: object)	yes
`RESOLUCION`	(inferred: object)	yes
`CONCLUIDO`	(inferred: bool)	no
`ENVIO CHEQUE`	(inferred: bool)	no
`NUM CHEQUE`	(inferred: float64)	no
`FECHA ACEPTACION`	(inferred: object)	yes
`FECHA REEMBOLSO`	(inferred: object)	yes
`SINIESTRO NUM`	(inferred: object)	yes
`CIA AJUSTADOR`	(inferred: object)	yes
`DOCS 1`	(inferred: object)	yes
`DOCS 2`	(inferred: object)	yes

`DATOS AUTOS`

Rows: 49 | Columns: 1

Column	Type	Nullable
`MARCA`	VARCHAR(50)	no

`DATOS AUTOS TIPO`

Rows: 133 | Columns: 1

Column	Type	Nullable
`TIPO`	VARCHAR(50)	no

`EDOSEG`

Rows: 5 | Columns: 18

Column	Type	Nullable
`NUMID`	DOUBLE(53)	no
`LETPOL`	VARCHAR(5)	no
`POLIZA`	DOUBLE(53)	no
`ASEGURADO`	VARCHAR(50)	yes
`PRIMA NETA`	DOUBLE(53)	no
`IVA`	DOUBLE(53)	no
`PRIMA TOTAL`	DOUBLE(53)	no
`DESDE`	DATETIME(19)	no
`HASTA`	DATETIME(19)	yes
`COMP`	VARCHAR(50)	no
`COM`	DOUBLE(53)	no
`FECHA1`	DATETIME(19)	yes
`FECHA2`	DATETIME(19)	yes
`F LIQUIDA1`	DATETIME(19)	yes
`F LIQUIDA2`	DATETIME(19)	yes
`FECHA PAGO`	DATETIME(19)	yes
`FECHA PAGO 2`	DATETIME(19)	yes
`FORMA PAGO`	VARCHAR(10)	no

`EFECTIVO`

Rows: 295 | Columns: 7

Column	Type	Nullable
`CL`	DOUBLE(53)	no
`FECHA`	DATETIME(19)	no
`MONTO`	DOUBLE(53)	no
`MONEDAS`	VARCHAR(50)	yes
`CONEPTO`	VARCHAR(100)	yes
`F DEPOSITO`	DATETIME(19)	yes
`FOLIO`	COUNTER(10)	no

`FECHAIF`

Rows: 1 | Columns: 2

Column	Type	Nullable
`FECHA INICIAL`	DATETIME(19)	no
`FECHA FINAL`	DATETIME(19)	no

`FECHAS EDOSEG`

Rows: 1 | Columns: 2

Column	Type	Nullable
`FECHA1`	DATETIME(19)	no
`FECHA2`	DATETIME(19)	no

`FECHAS PRIMA NETA`

Rows: 1 | Columns: 2

Column	Type	Nullable
`FECHA1`	DATETIME(19)	no
`FECHA2`	DATETIME(19)	no

`FORMAS`

Rows: 11 | Columns: 1

Column	Type	Nullable
`FORMA`	VARCHAR(50)	no

`IMPUESTOS`

Rows: 1 | Columns: 1

Column	Type	Nullable
`IVA`	DOUBLE(53)	no

`IMPUESTOS_AUTOS`

Rows: 1 | Columns: 1

Column	Type	Nullable
`IVA`	DOUBLE(53)	no

`INCENDIO`

Rows: 1 | Columns: 57

Column	Type	Nullable
`NUM id`	DOUBLE(53)	no
`LETPOL`	VARCHAR(2)	no
`NO POLIZA`	INTEGER(10)	no
`FOLIO`	INTEGER(10)	no
`NOMBRE ASEG`	VARCHAR(50)	no
`COMP`	VARCHAR(50)	no
`AGENT`	VARCHAR(20)	no
`DESDE`	DATETIME(19)	no
`HASTA`	DATETIME(19)	no
`FORMA PAGO`	VARCHAR(10)	no
`VIG 1`	DATETIME(19)	no
`VIG 2`	DATETIME(19)	yes
`VIG 3`	DATETIME(19)	yes
`VIG 4`	DATETIME(19)	yes
`MONEDA`	VARCHAR(7)	no
`1ER PAGO`	DOUBLE(53)	no
`PAGO SUBSEC`	DOUBLE(53)	no
`FECHA PAGO`	DATETIME(19)	no
`EFECTIVO`	BIT(1)	no
`NO CHEQUE`	VARCHAR(4)	yes
`FECHA PAGO 2`	DATETIME(19)	yes
`MONED 2`	VARCHAR(7)	yes
`EFECTIVO 2`	BIT(1)	no
`NO CHEQUE 2`	VARCHAR(50)	yes
`FECHA PAGO 3`	DATETIME(19)	yes
`MONED 3`	VARCHAR(7)	yes
`EFECTIVO 3`	BIT(1)	no
`NO CHEQUE 3`	VARCHAR(50)	yes
`FECHA PAGO 4`	DATETIME(19)	yes
`MONED 4`	VARCHAR(7)	yes
`EFECTIVO 4`	BIT(1)	no
`NO CHEQUE 4`	VARCHAR(50)	yes
`P NETA`	DOUBLE(53)	no
`P NETA 2`	DOUBLE(53)	no
`RECARGO`	DOUBLE(53)	no
`RECARGO 2`	DOUBLE(53)	no
`D POL`	DOUBLE(53)	no
`D POL 2`	DOUBLE(53)	no
`COM`	DOUBLE(53)	no
`COM 2`	DOUBLE(53)	no
`LIQUIDADA`	BIT(1)	no
`LIQUIDADA 2`	BIT(1)	no
`EDIFICIO`	DOUBLE(53)	no
`EDIF TERREMOTO`	BIT(1)	no
`CONTENIDOS`	DOUBLE(53)	no
`CONT TERREMOTO`	BIT(1)	no
`CONSTRUCCION`	LONGCHAR(1073741823)	yes
`OBSERVACIONES`	LONGCHAR(1073741823)	yes
`RENOVACION`	DOUBLE(53)	no
`NUM LIQUIDACION`	VARCHAR(50)	no
`NUM LIQUIDACION2`	VARCHAR(50)	yes
`F LIQUIDA1`	DATETIME(19)	no
`F LIQUIDA2`	DATETIME(19)	yes
`CALLE Y NO`	VARCHAR(30)	yes
`COL`	VARCHAR(30)	yes
`EDO`	VARCHAR(2)	yes
`TEL`	VARCHAR(8)	yes

`LICENCIAS`

Rows: 309 | Columns: 51

Column	Type	Nullable
`NO POLIZA`	VARCHAR(50)	no
`FOLIO`	INTEGER(10)	yes
`NUMER ID`	DOUBLE(53)	no
`P ANTERIOR`	INTEGER(10)	yes
`LETPOL`	VARCHAR(4)	no
`CALLE Y NO`	VARCHAR(30)	yes
`COL`	VARCHAR(15)	yes
`EDO`	VARCHAR(2)	no
`TEL`	VARCHAR(8)	yes
`COMP`	VARCHAR(30)	yes
`CONTR`	DOUBLE(53)	no
`AGENT`	VARCHAR(20)	yes
`DESDE`	DATETIME(19)	no
`HASTA`	DATETIME(19)	yes
`FORMA PAGO`	VARCHAR(10)	yes
`MONEDA`	VARCHAR(7)	no
`FECHA PAGO`	DATETIME(19)	yes
`EFECTIVO`	BIT(1)	no
`NO CHEQUE`	VARCHAR(4)	yes
`OBSERVACIONES`	LONGCHAR(1073741823)	yes
`COBERTURA`	INTEGER(10)	yes
`NOMBRE ASEG 1`	VARCHAR(30)	yes
`LIC 1`	VARCHAR(20)	yes
`EDO 1`	VARCHAR(2)	yes
`NOMBRE ASEG 2`	VARCHAR(30)	yes
`LIC 2`	VARCHAR(20)	yes
`EDO 2`	VARCHAR(2)	yes
`NOMBRE ASEG 3`	VARCHAR(30)	yes
`LIC 3`	VARCHAR(20)	yes
`EDO 3`	VARCHAR(2)	yes
`PROPIEDADES`	DOUBLE(53)	yes
`PERSONAS`	DOUBLE(53)	yes
`CSL LIMITE`	INTEGER(10)	yes
`GASTOS MEDICO`	DOUBLE(53)	yes
`SERVICIO ADICIONAL`	BIT(1)	no
`CLAVE`	DOUBLE(53)	yes
`HORA`	DATETIME(19)	yes
`$ TOT`	DOUBLE(53)	no
`PRIMA NETA`	DOUBLE(53)	no
`D POLIZA`	DOUBLE(53)	no
`TOTAL`	DOUBLE(53)	no
`ACCIDENTE`	DOUBLE(53)	no
`RENOVACION`	DOUBLE(53)	no
`LIQUIDADA`	BIT(1)	no
`NUM LIQUIDACION`	VARCHAR(50)	yes
`F LIQUIDA1`	DATETIME(19)	yes
`F EMISION`	DATETIME(19)	no
`ENDOSO`	BIT(1)	no
`CONFIRMA L1`	DATETIME(19)	yes
`SERV CIA`	BIT(1)	no
`RENT`	BIT(1)	no

`LIQUIDA SELLO`

Rows: 1 | Columns: 4

Column	Type	Nullable
`TECLEE LIQUIDACION`	VARCHAR(50)	no
`FECHA SELLO`	DATETIME(19)	no
`CH COMISION1N`	VARCHAR(50)	no
`CH COMISION1F`	DATETIME(19)	no

`LIQUIDAAD`

Rows: 7 | Columns: 6

Column	Type	Nullable
`POLIZA`	VARCHAR(50)	no
`VIGENCIA INICIAL`	DATETIME(19)	no
`PRIMA NETA`	DOUBLE(53)	no
`DERECHO DE PÓLIZA`	DOUBLE(53)	no
`COM`	DOUBLE(53)	no
`OBSERVACIONES`	VARCHAR(50)	no

`M EMPR`

Rows: 5 | Columns: 73

Column	Type	Nullable
`NUM id`	DOUBLE(53)	no
`LETPOL`	VARCHAR(2)	no
`NO POLIZA`	INTEGER(10)	no
`FOLIO`	INTEGER(10)	no
`NOMBRE ASEG`	VARCHAR(50)	no
`COMP`	VARCHAR(50)	no
`AGENT`	VARCHAR(20)	yes
`DESDE`	DATETIME(19)	no
`HASTA`	DATETIME(19)	yes
`FORMA PAGO`	VARCHAR(10)	no
`VIG 1`	DATETIME(19)	yes
`VIG 2`	DATETIME(19)	yes
`VIG 3`	DATETIME(19)	yes
`VIG 4`	DATETIME(19)	yes
`1ER PAGO`	DOUBLE(53)	no
`FECHA PAGO`	DATETIME(19)	yes
`MONED`	VARCHAR(7)	yes
`EFECTIVO`	BIT(1)	no
`NO CHEQUE`	VARCHAR(4)	yes
`PAGO SUBSEC`	DOUBLE(53)	no
`FECHA PAGO 2`	DATETIME(19)	yes
`MONED 2`	VARCHAR(7)	yes
`EFECTIVO 2`	BIT(1)	no
`NO CHEQUE 2`	VARCHAR(50)	yes
`FECHA PAGO 3`	DATETIME(19)	yes
`MONED 3`	VARCHAR(7)	yes
`EFECTIVO 3`	BIT(1)	no
`NO CHEQUE 3`	VARCHAR(50)	yes
`FECHA PAGO 4`	DATETIME(19)	yes
`MONED 4`	VARCHAR(7)	yes
`EFECTIVO 4`	BIT(1)	no
`NO CHEQUE 4`	VARCHAR(50)	yes
`P NETA`	DOUBLE(53)	no
`P NETA 2`	DOUBLE(53)	no
`RECARGO`	DOUBLE(53)	no
`RECARGO 2`	DOUBLE(53)	no
`D POL`	DOUBLE(53)	no
`D POL 2`	DOUBLE(53)	no
`COM`	DOUBLE(53)	no
`COM 2`	DOUBLE(53)	no
`LIQUIDADA`	BIT(1)	no
`LIQUIDADA 2`	BIT(1)	no
`LIQUIDADA 3`	BIT(1)	no
`LIQUIDADA 4`	BIT(1)	no
`EDIFICIO`	DOUBLE(53)	no
`EDIF TERREMOTO`	BIT(1)	no
`CONTENIDOS`	DOUBLE(53)	no
`CONT TERREMOTO`	BIT(1)	no
`R CIVIL ACT`	DOUBLE(53)	no
`R CIVIL ARREND`	DOUBLE(53)	no
`ROBO C VIOLENCIA`	DOUBLE(53)	no
`CRISTALES`	DOUBLE(53)	no
`ANUNCIOS LUM`	INTEGER(10)	no
`DIN Y VALORES`	INTEGER(10)	no
`PLANTA BAJA`	VARCHAR(50)	yes
`PLANTA ALTA`	VARCHAR(50)	yes
`CONSTRUCCION`	LONGCHAR(1073741823)	yes
`OBSERVACIONES`	LONGCHAR(1073741823)	yes
`RENOVACION`	DOUBLE(53)	no
`NUM LIQUIDACION`	VARCHAR(50)	yes
`NUM LIQUIDACION2`	VARCHAR(50)	yes
`NUM LIQUIDACION3`	VARCHAR(50)	yes
`NUM LIQUIDACION4`	VARCHAR(50)	yes
`F LIQUIDA1`	DATETIME(19)	yes
`F LIQUIDA2`	DATETIME(19)	yes
`F LIQUIDA3`	DATETIME(19)	yes
`F LIQUIDA4`	DATETIME(19)	yes
`CALLE Y NO`	VARCHAR(30)	no
`COL`	VARCHAR(30)	yes
`EDO`	VARCHAR(2)	yes
`TEL`	VARCHAR(8)	yes
`CONFIRMA L1`	DATETIME(19)	yes
`CONFIRMA L2`	DATETIME(19)	yes

`MCA2`

Rows: 4 | Columns: 83

Column	Type	Nullable
`NUMER ID`	DOUBLE(53)	no
`LETPOL`	VARCHAR(3)	no
`POLIZA`	VARCHAR(50)	no
`FOLIO`	INTEGER(10)	no
`COMP`	VARCHAR(50)	no
`AGENT`	VARCHAR(20)	yes
`DESDE`	DATETIME(19)	no
`HASTA`	DATETIME(19)	yes
`COBERTURA`	INTEGER(10)	no
`FORMA PAGO`	VARCHAR(10)	yes
`1ER PAGO`	DOUBLE(53)	no
`FECHA PAGO`	DATETIME(19)	yes
`MONED`	VARCHAR(7)	yes
`EFECTIVO`	BIT(1)	no
`NO CHEQUE`	VARCHAR(4)	yes
`PROPIEDADES`	DOUBLE(53)	no
`PERSONAS`	DOUBLE(53)	no
`GASTOS MEDICO`	DOUBLE(53)	no
`AÑO1`	VARCHAR(2)	yes
`MARCA1`	VARCHAR(15)	no
`MODELO1`	VARCHAR(15)	no
`AUTO ID1`	VARCHAR(20)	no
`CLASE1`	VARCHAR(50)	yes
`PLACA1`	VARCHAR(7)	yes
`EDO1`	VARCHAR(2)	yes
`AÑO2`	VARCHAR(2)	yes
`MARCA2`	VARCHAR(15)	yes
`MODELO2`	VARCHAR(15)	yes
`AUTO ID2`	VARCHAR(20)	yes
`CLASE2`	VARCHAR(50)	yes
`PLACA2`	VARCHAR(7)	yes
`EDO2`	VARCHAR(2)	yes
`AÑO3`	VARCHAR(2)	yes
`MARCA3`	VARCHAR(15)	yes
`MODELO3`	VARCHAR(15)	yes
`AUTO ID3`	VARCHAR(20)	yes
`CLASE3`	VARCHAR(50)	yes
`PLACA3`	VARCHAR(7)	yes
`EDO3`	VARCHAR(2)	yes
`PRIMA1`	CURRENCY(19)	yes
`D POLIZA1`	CURRENCY(19)	yes
`NAME1`	VARCHAR(40)	yes
`BIRTH1`	DATETIME(19)	yes
`EDAD1`	VARCHAR(2)	yes
`LIC1`	VARCHAR(20)	yes
`LICEDO1`	VARCHAR(2)	yes
`OCUP1`	VARCHAR(50)	yes
`NAME2`	VARCHAR(40)	yes
`BIRTH2`	DATETIME(19)	yes
`EDAD2`	VARCHAR(2)	yes
`LIC2`	VARCHAR(20)	yes
`LICEDO2`	VARCHAR(2)	yes
`OCUP2`	VARCHAR(50)	yes
`NAME3`	VARCHAR(40)	yes
`BIRTH3`	DATETIME(19)	yes
`EDAD3`	VARCHAR(2)	yes
`LIC3`	VARCHAR(20)	yes
`LICEDO3`	VARCHAR(2)	yes
`OCUP3`	VARCHAR(50)	yes
`POLIZA ANT`	VARCHAR(10)	yes
`FECHA PAGO`	DATETIME(19)	yes
`PAGO`	DOUBLE(53)	no
`CHEQUE`	VARCHAR(4)	yes
`LIQUIDADA`	BIT(1)	no
`OB1`	LONGCHAR(1073741823)	yes
`OB2`	LONGCHAR(1073741823)	yes
`OB3`	LONGCHAR(1073741823)	yes
`PRIMA CO`	DOUBLE(53)	yes
`D POLIZA CO`	DOUBLE(53)	yes
`NULIQUIDA`	VARCHAR(50)	yes
`RENOVACION`	DOUBLE(53)	yes
`CSL LIMITE`	INTEGER(10)	no
`F LIQUIDA1`	DATETIME(19)	yes
`CONTR`	DOUBLE(53)	no
`DIAS`	BIT(1)	no
`SEX1`	VARCHAR(1)	yes
`SEX2`	VARCHAR(1)	yes
`AM`	BIT(1)	no
`HORA1`	VARCHAR(5)	no
`HORA2`	VARCHAR(5)	no
`MP`	DOUBLE(53)	yes
`CONFIRMA L1`	DATETIME(19)	yes
`RENT`	BIT(1)	no

`MULT`

Rows: 763 | Columns: 82

Column	Type	Nullable
`NUM id`	DOUBLE(53)	no
`LETPOL`	VARCHAR(2)	no
`NO POLIZA`	DOUBLE(53)	no
`FOLIO`	VARCHAR(50)	yes
`NOMBRE ASEG`	VARCHAR(50)	yes
`COMP`	VARCHAR(50)	no
`AGENT`	VARCHAR(20)	no
`DESDE`	DATETIME(19)	yes
`HASTA`	DATETIME(19)	yes
`FORMA PAGO`	VARCHAR(10)	yes
`VIG 1`	DATETIME(19)	yes
`VIG 2`	DATETIME(19)	yes
`VIG 3`	DATETIME(19)	yes
`VIG 4`	DATETIME(19)	yes
`1ER PAGO`	DOUBLE(53)	no
`FECHA PAGO`	DATETIME(19)	yes
`MONED`	VARCHAR(7)	yes
`EFECTIVO`	BIT(1)	no
`NO CHEQUE`	VARCHAR(4)	yes
`PAGO SUBSEC`	DOUBLE(53)	yes
`FECHA PAGO 2`	DATETIME(19)	yes
`MONED 2`	VARCHAR(7)	yes
`EFECTIVO 2`	BIT(1)	no
`NO CHEQUE 2`	VARCHAR(50)	yes
`FECHA PAGO 3`	DATETIME(19)	yes
`MONED 3`	VARCHAR(7)	yes
`EFECTIVO 3`	BIT(1)	no
`NO CHEQUE 3`	VARCHAR(50)	yes
`FECHA PAGO 4`	DATETIME(19)	yes
`MONED 4`	VARCHAR(7)	yes
`EFECTIVO 4`	BIT(1)	no
`NO CHEQUE 4`	VARCHAR(50)	yes
`P NETA`	DOUBLE(53)	no
`P NETA 2`	DOUBLE(53)	yes
`RECARGO`	DOUBLE(53)	no
`RECARGO 2`	DOUBLE(53)	yes
`D POL`	DOUBLE(53)	no
`D POL 2`	DOUBLE(53)	no
`COM`	DOUBLE(53)	no
`COM 2`	DOUBLE(53)	yes
`LIQUIDADA`	BIT(1)	no
`LIQUIDADA 2`	BIT(1)	no
`EDIFICIO`	DOUBLE(53)	yes
`EDIF TERREMOTO`	BIT(1)	no
`CONTENIDOS`	DOUBLE(53)	no
`CONT TERREMOTO`	BIT(1)	no
`R CIVIL FAMILIAR`	DOUBLE(53)	no
`R CIVIL ARREND`	DOUBLE(53)	yes
`ROBO C VIOLENCIA`	DOUBLE(53)	yes
`CRISTALES`	DOUBLE(53)	no
`PLANTA BAJA`	VARCHAR(50)	yes
`PLANTA ALTA`	VARCHAR(50)	yes
`CONSTRUCCION`	LONGCHAR(1073741823)	yes
`OBSERVACIONES`	LONGCHAR(1073741823)	yes
`RENOVACION`	DOUBLE(53)	yes
`NUM LIQUIDACION`	VARCHAR(50)	yes
`NUM LIQUIDACION2`	VARCHAR(50)	yes
`F LIQUIDA1`	DATETIME(19)	yes
`F LIQUIDA2`	DATETIME(19)	yes
`CALLE Y NO`	VARCHAR(30)	yes
`COL`	VARCHAR(30)	yes
`EDO`	VARCHAR(2)	yes
`CP`	VARCHAR(50)	yes
`TEL`	VARCHAR(8)	yes
`CONDO`	BIT(1)	no
`TIPO`	VARCHAR(50)	yes
`DESCR EDIFICIO`	VARCHAR(100)	yes
`MUROS`	VARCHAR(100)	yes
`TECHO`	VARCHAR(100)	yes
`HIDR`	BIT(1)	no
`FOTO1`	LONGBINARY(1073741823)	yes
`CONFIRMA L1`	DATETIME(19)	yes
`CONFIRMA L2`	DATETIME(19)	yes
`CH CONF L1N`	VARCHAR(50)	yes
`CH CONF L2N`	VARCHAR(50)	yes
`CH COMISION1NU`	VARCHAR(50)	yes
`CH COMISION2NU`	VARCHAR(50)	yes
`COMISION2FE`	DATETIME(19)	yes
`COMISION1FE`	DATETIME(19)	yes
`COPIA B`	VARCHAR(2)	yes
`DOCS 1`	LONGBINARY(1073741823)	yes
`DOCS 2`	LONGBINARY(1073741823)	yes

`RECIBONOCLIENT`

Rows: 1 | Columns: 4

Column	Type	Nullable
`NOMBRE CLIENTE`	VARCHAR(50)	no
`CONCEPTO`	VARCHAR(200)	no
`CANTIDAD`	DOUBLE(53)	no
`MONEDAS`	VARCHAR(50)	no

`TABLA AUTOS`

Rows: 804 | Columns: 55

Column	Type	Nullable
`NUMER ID`	DOUBLE(53)	no
`LETPOL`	VARCHAR(4)	no
`NO POLIZA`	VARCHAR(50)	no
`P ANTERIOR`	INTEGER(10)	yes
`FOLIO`	INTEGER(10)	yes
`NOMBRE ASEG`	VARCHAR(50)	yes
`CALLE Y NO`	VARCHAR(30)	yes
`COL`	VARCHAR(15)	yes
`EDO`	VARCHAR(2)	no
`TEL`	VARCHAR(8)	yes
`COMP`	VARCHAR(30)	yes
`AGENT`	VARCHAR(20)	yes
`DESDE`	DATETIME(19)	yes
`HASTA`	DATETIME(19)	yes
`FORMA PAGO`	VARCHAR(10)	yes
`CONTR`	DOUBLE(53)	yes
`MONEDA`	VARCHAR(7)	yes
`FECHA PAGO`	DATETIME(19)	yes
`EFECTIVO`	BIT(1)	no
`NO CHEQUE`	VARCHAR(4)	yes
`MARCA 1`	VARCHAR(20)	yes
`MODELO 1`	VARCHAR(2)	yes
`CARROCERIA 1`	VARCHAR(20)	yes
`MOTOR 1`	VARCHAR(20)	yes
`PLACA 1`	VARCHAR(50)	yes
`MARCA 2`	VARCHAR(20)	yes
`MODELO 2`	VARCHAR(4)	yes
`CARROCERIA 2`	VARCHAR(20)	yes
`MOTOR 2`	VARCHAR(20)	yes
`PLACA 2`	VARCHAR(50)	yes
`MARCA 3`	VARCHAR(50)	yes
`MODELO 3`	VARCHAR(50)	yes
`CARROCERIA 3`	VARCHAR(50)	yes
`MOTOR 3`	VARCHAR(50)	yes
`OBSERVACIONES`	LONGCHAR(1073741823)	yes
`COBERTURA`	INTEGER(10)	yes
`PROPIEDADES`	DOUBLE(53)	yes
`PERSONAS`	DOUBLE(53)	yes
`CSL LIMITE`	INTEGER(10)	yes
`GASTOS MEDICO`	DOUBLE(53)	yes
`SERVICIO ADICIONAL`	BIT(1)	no
`CLAVE`	DOUBLE(53)	no
`HORA`	DATETIME(19)	yes
`PRIMA NETA`	DOUBLE(53)	no
`D POLIZA`	DOUBLE(53)	no
`TOTAL`	DOUBLE(53)	no
`LIQUIDADA`	BIT(1)	no
`RENOVACION`	DOUBLE(53)	yes
`F EMISION`	DATETIME(19)	yes
`ENDOSO`	BIT(1)	no
`NUM LIQUIDACION`	VARCHAR(50)	yes
`F LIQUIDA1`	DATETIME(19)	yes
`CONFIRMA L1`	DATETIME(19)	yes
`SERV CIA`	BIT(1)	no
`RENT`	BIT(1)	no

`TABLA AUTOS AMPL`

Rows: 478 | Columns: 61

Column	Type	Nullable
`NUMER ID`	DOUBLE(53)	no
`LETPOL`	VARCHAR(4)	no
`NO POLIZA`	VARCHAR(50)	no
`P ANTERIOR`	INTEGER(10)	yes
`FOLIO`	INTEGER(10)	no
`NOMBRE ASEG`	VARCHAR(50)	yes
`CALLE Y NO`	VARCHAR(30)	yes
`COL`	VARCHAR(15)	yes
`EDO`	VARCHAR(2)	no
`TEL`	VARCHAR(8)	yes
`COMP`	VARCHAR(30)	yes
`CONTR`	DOUBLE(53)	yes
`AGENT`	VARCHAR(20)	yes
`DESDE`	DATETIME(19)	yes
`HASTA`	DATETIME(19)	yes
`FORMA PAGO`	VARCHAR(10)	no
`MONEDA`	VARCHAR(7)	no
`FECHA PAGO`	DATETIME(19)	yes
`EFECTIVO`	BIT(1)	no
`NO CHEQUE`	VARCHAR(4)	yes
`MARCA`	VARCHAR(20)	yes
`MODELO`	VARCHAR(2)	yes
`CARROCERIA`	VARCHAR(20)	yes
`MOTOR`	VARCHAR(20)	yes
`PLACA`	VARCHAR(50)	yes
`COLISION`	DOUBLE(53)	yes
`SUMA ROBO`	DOUBLE(53)	yes
`GASTOS MEDICO`	DOUBLE(53)	yes
`ENDOSO`	BIT(1)	no
`OBSERVACIONES`	LONGCHAR(1073741823)	yes
`COBERTURA`	INTEGER(10)	yes
`PROPIEDADES`	DOUBLE(53)	yes
`PERSONAS`	DOUBLE(53)	yes
`CSL LIMITE`	INTEGER(10)	yes
`SERVICIO ADICIONAL`	BIT(1)	no
`CLAVE`	DOUBLE(53)	yes
`HORA`	DATETIME(19)	yes
`PRIMA NETA`	DOUBLE(53)	no
`D POLIZA`	DOUBLE(53)	no
`TOTAL`	DOUBLE(53)	no
`LIQUIDADA`	BIT(1)	no
`RENOVACION`	DOUBLE(53)	yes
`EXTENDED COVERAGE`	BIT(1)	no
`F EMISION`	DATETIME(19)	no
`CUBIERTO CON`	VARCHAR(10)	yes
`NUM LIQUIDACION`	VARCHAR(50)	yes
`F LIQUIDA1`	DATETIME(19)	yes
`ROBO%`	DOUBLE(53)	no
`COLI%`	DOUBLE(53)	no
`SERV CIA`	BIT(1)	no
`FOTO1`	LONGBINARY(1073741823)	yes
`CONFIRMA L1`	DATETIME(19)	yes
`PLACAS`	VARCHAR(50)	yes
`D MATERIAL`	VARCHAR(50)	yes
`R TOTAL`	VARCHAR(50)	yes
`VALOR AUTO`	DOUBLE(53)	yes
`LOSS`	BIT(1)	no
`RENT`	BIT(1)	no
`COPIA B`	VARCHAR(2)	yes
`DOCS 1`	LONGBINARY(1073741823)	yes
`DOCS 2`	LONGBINARY(1073741823)	yes

`TABLA AUTOS AMPL R`

Rows: 14 | Columns: 56

Column	Type	Nullable
`NUMER ID`	DOUBLE(53)	no
`LETPOL`	VARCHAR(4)	no
`NO POLIZA`	VARCHAR(50)	no
`NOMBRE ASEG`	VARCHAR(50)	no
`CALLE Y NO`	VARCHAR(30)	yes
`COL`	VARCHAR(15)	yes
`EDO`	VARCHAR(2)	no
`TEL`	VARCHAR(8)	yes
`COM`	DOUBLE(53)	yes
`COM 2`	DOUBLE(53)	yes
`COMP`	VARCHAR(30)	no
`AGENT`	VARCHAR(20)	yes
`DESDE`	DATETIME(19)	no
`HASTA`	DATETIME(19)	yes
`VIG 1`	DATETIME(19)	yes
`VIG 2`	DATETIME(19)	yes
`1ER PAGO`	DOUBLE(53)	yes
`FORMA PAGO`	VARCHAR(10)	no
`MONEDA`	VARCHAR(7)	no
`FECHA PAGO`	DATETIME(19)	yes
`EFECTIVO`	BIT(1)	no
`NO CHEQUE`	VARCHAR(4)	yes
`PAGO SUBSEC`	DOUBLE(53)	yes
`FECHA PAGO 2`	DATETIME(19)	yes
`MONED 2`	VARCHAR(7)	yes
`EFECTIVO 2`	BIT(1)	no
`NO CHEQUE 2`	VARCHAR(50)	yes
`MARCA`	VARCHAR(20)	no
`MODELO`	VARCHAR(2)	yes
`CARROCERIA`	VARCHAR(20)	no
`MOTOR`	VARCHAR(20)	no
`COLISION`	VARCHAR(50)	no
`SUMA ROBO`	VARCHAR(50)	no
`GASTOS MEDICO`	DOUBLE(53)	no
`OBSERVACIONES`	LONGCHAR(1073741823)	yes
`COBERTURA`	INTEGER(10)	no
`PROPIEDADES`	DOUBLE(53)	no
`CLAVE`	DOUBLE(53)	yes
`PRIMA NETA`	DOUBLE(53)	no
`PRIMA NETA2`	DOUBLE(53)	yes
`RECARGO`	DOUBLE(53)	no
`RECARGO 2`	DOUBLE(53)	yes
`D POLIZA`	DOUBLE(53)	no
`D POLIZA2`	DOUBLE(53)	yes
`LIQUIDADA`	BIT(1)	no
`LIQUIDADA 2`	BIT(1)	no
`RENOVACION`	DOUBLE(53)	yes
`A JURIDICA`	BIT(1)	no
`A CAMINO`	BIT(1)	no
`NUM LIQUIDACION`	VARCHAR(50)	yes
`NUM LIQUIDACION2`	VARCHAR(50)	yes
`F LIQUIDA1`	DATETIME(19)	yes
`F LIQUIDA2`	DATETIME(19)	yes
`CONFIRMA L1`	DATETIME(19)	yes
`CONFIRMA L2`	DATETIME(19)	yes
`RENT`	BIT(1)	no

`TABLA AUTOS LIMIT`

Rows: 1 | Columns: 38

Column	Type	Nullable
`NUMER ID`	DOUBLE(53)	no
`LETPOL`	VARCHAR(4)	no
`NO POLIZA`	INTEGER(10)	no
`FOLIO`	INTEGER(10)	no
`CALLE Y NO`	VARCHAR(30)	yes
`COL`	VARCHAR(15)	yes
`EDO`	VARCHAR(2)	no
`TEL`	VARCHAR(8)	yes
`COMP`	VARCHAR(30)	no
`CONTR`	DOUBLE(53)	no
`AGENT`	VARCHAR(20)	no
`DESDE`	DATETIME(19)	no
`HASTA`	DATETIME(19)	no
`FORMA PAGO`	VARCHAR(10)	no
`MONEDA`	VARCHAR(7)	no
`FECHA PAGO`	DATETIME(19)	yes
`EFECTIVO`	BIT(1)	no
`NO CHEQUE`	VARCHAR(4)	yes
`MARCA`	VARCHAR(20)	no
`MODELO`	VARCHAR(2)	no
`CARROCERIA`	VARCHAR(20)	no
`MOTOR`	VARCHAR(20)	no
`SUMA ROBO`	DOUBLE(53)	no
`GASTOS MEDICO`	DOUBLE(53)	no
`ENDOSO`	BIT(1)	no
`OBSERVACIONES`	LONGCHAR(1073741823)	yes
`COBERTURA`	INTEGER(10)	no
`PROPIEDADES`	DOUBLE(53)	no
`PERSONAS`	DOUBLE(53)	no
`SERVICIO ADICIONAL`	BIT(1)	no
`CLAVE`	DOUBLE(53)	no
`HORA`	DATETIME(19)	no
`PRIMA NETA`	DOUBLE(53)	no
`D POLIZA`	DOUBLE(53)	no
`IVA`	DOUBLE(53)	no
`TOTAL`	DOUBLE(53)	no
`LIQUIDADA`	BIT(1)	no
`RENOVACION`	DOUBLE(53)	no

`TABLA AUTOS RC R`

Rows: 8 | Columns: 57

Column	Type	Nullable
`NUMER ID`	DOUBLE(53)	no
`LETPOL`	VARCHAR(4)	no
`NO POLIZA`	VARCHAR(50)	no
`NOMBRE ASEG`	VARCHAR(50)	yes
`CALLE Y NO`	VARCHAR(30)	yes
`COL`	VARCHAR(15)	yes
`EDO`	VARCHAR(2)	no
`TEL`	VARCHAR(8)	yes
`COMP`	VARCHAR(30)	yes
`COM`	DOUBLE(53)	yes
`COM 2`	DOUBLE(53)	yes
`AGENT`	VARCHAR(20)	yes
`DESDE`	DATETIME(19)	no
`HASTA`	DATETIME(19)	yes
`VIG 1`	DATETIME(19)	yes
`1ER PAGO`	DOUBLE(53)	no
`FORMA PAGO`	VARCHAR(10)	no
`MONEDA`	VARCHAR(7)	no
`FECHA PAGO`	DATETIME(19)	yes
`EFECTIVO`	BIT(1)	no
`NO CHEQUE`	VARCHAR(4)	yes
`PAGO SUBSEC`	DOUBLE(53)	yes
`FECHA PAGO 2`	DATETIME(19)	yes
`MONED 2`	VARCHAR(7)	yes
`EFECTIVO 2`	BIT(1)	no
`NO CHEQUE 2`	VARCHAR(50)	yes
`MARCA`	VARCHAR(20)	yes
`MODELO`	VARCHAR(2)	yes
`CARROCERIA`	VARCHAR(20)	yes
`MOTOR`	VARCHAR(20)	yes
`GASTOS MEDICO`	DOUBLE(53)	no
`ENDOSO`	BIT(1)	no
`OBSERVACIONES`	LONGCHAR(1073741823)	no
`COBERTURA`	INTEGER(10)	no
`PROPIEDADES`	DOUBLE(53)	no
`SERVICIO ADICIONAL`	BIT(1)	no
`CLAVE`	DOUBLE(53)	yes
`HORA`	DATETIME(19)	no
`PRIMA NETA`	DOUBLE(53)	no
`PRIMA NETA2`	DOUBLE(53)	no
`RECARGO`	DOUBLE(53)	no
`RECARGO 2`	DOUBLE(53)	no
`D POLIZA`	DOUBLE(53)	no
`D POLIZA2`	DOUBLE(53)	no
`LIQUIDADA`	BIT(1)	no
`LIQUIDADA 2`	BIT(1)	no
`RENOVACION`	DOUBLE(53)	yes
`A JURIDICA`	BIT(1)	no
`A CAMINO`	BIT(1)	no
`F EMISION`	DATETIME(19)	no
`NUM LIQUIDACION`	VARCHAR(50)	yes
`NUM LIQUIDACION2`	VARCHAR(50)	yes
`F LIQUIDA1`	DATETIME(19)	yes
`F LIQUIDA2`	DATETIME(19)	yes
`CONFIRMA L1`	DATETIME(19)	yes
`CONFIRMA L2`	DATETIME(19)	yes
`RENT`	BIT(1)	no

`TABLE DATOS LIQUIDA MCA2`

Rows: 1 | Columns: 7

Column	Type	Nullable
`COMPANIA`	VARCHAR(50)	no
`AGENTE`	VARCHAR(50)	no
`CLAVE`	DOUBLE(53)	no
`CONTROL`	VARCHAR(50)	no
`FECHA INI`	DATETIME(19)	no
`FECHA FIN`	DATETIME(19)	no
`MENSAJE`	LONGCHAR(1073741823)	yes

`TABLE DATOS LIQUIDA MF`

Rows: 1 | Columns: 5

Column	Type	Nullable
`COMPANIA`	VARCHAR(50)	no
`AGENTE`	VARCHAR(50)	no
`CONTROL`	VARCHAR(50)	no
`FECHA INI`	DATETIME(19)	no
`FECHA FIN`	DATETIME(19)	no

`TABLE DATOS LIQUIDA RES`

Rows: 1 | Columns: 6

Column	Type	Nullable
`COMPANIA`	VARCHAR(50)	no
`AGENTE`	VARCHAR(50)	no
`CLAVE`	DOUBLE(53)	no
`CONTROL`	VARCHAR(50)	no
`FECHA INI`	DATETIME(19)	no
`FECHA FIN`	DATETIME(19)	no

`TABLE DATOS LIQUIDA TUR`

Rows: 1 | Columns: 7

Column	Type	Nullable
`COMPANIA`	VARCHAR(50)	no
`AGENTE`	VARCHAR(50)	no
`CLAVE`	DOUBLE(53)	no
`CONTROL`	VARCHAR(50)	no
`FECHA INI`	DATETIME(19)	no
`FECHA FIN`	DATETIME(19)	no
`EXT COVERAGE`	DOUBLE(53)	yes

`TIPOS`

Rows: 4 | Columns: 1

Column	Type	Nullable
`TIPO`	VARCHAR(50)	no

`UTILSEG`

Rows: 1582 | Columns: 3

Column	Type	Nullable
`NOMBRE`	VARCHAR(50)	yes
`SEGUROS`	INTEGER(10)	yes
`UTIL`	INTEGER(10)	yes

`gen1`

Rows: 9 | Columns: 6

Column	Type	Nullable
`RFC`	VARCHAR(50)	yes
`CLAVE`	DOUBLE(53)	yes
`COMP`	VARCHAR(30)	yes
`FPAGO`	VARCHAR(10)	yes
`MONED`	VARCHAR(7)	yes
`gen2_ID`	INTEGER(10)	no

`gen2`

Rows: 14 | Columns: 2

Column	Type	Nullable
`AGENT`	VARCHAR(20)	yes
`ID`	COUNTER(10)	no

Excluded tables

Table	Rows
`AMPL MENS`	1
`AMPL R MENS`	1
`BORRA`	1
`GENERICO_OLD`	6
`ID TABLA`	0
`ID TABLATLAS`	0
`IN MENS`	1
`LIC MENS`	1
`MCA2 MENS`	1
`ME MENS`	1
`MF MENS`	1
`RC MENSAJE`	1
`RC R MENS`	1
`TABLA AUTOS LIMIT R`	0
`TABLA LIQUIDA MCA2`	0
`TABLA LIQUIDA MF`	0
`TABLA LIQUIDA RES`	0
`TABLA LIQUIDA TUR`	0
`TABLA LIQUIDA TUR ENDOSO`	0
`TIT`	1
`TODOS`	0
`TODOSJC`	569
`vigenta casa y auto unicos`	1733

SCOTHIA.mdb

7 tables total — 4 included in migration, 3 excluded (scratch/template/report tables).

`DATOS E`

Rows: 15406 | Columns: 8

Column	Type	Nullable
`FECHA`	DATETIME(19)	no
`TIPO`	VARCHAR(50)	no
`NUM`	DOUBLE(53)	yes
`CONCEPTO`	VARCHAR(50)	yes
`EGRESO`	DOUBLE(53)	no
`OPERADO`	BIT(1)	no
`NOTAS`	VARCHAR(100)	yes
`CANTIDAD EN LETRA`	VARCHAR(100)	yes

`DATOS I`

Rows: 6948 | Columns: 8

Column	Type	Nullable
`FECHA`	DATETIME(19)	no
`TIPO`	VARCHAR(50)	no
`NUM`	DOUBLE(53)	yes
`CONCEPTO`	VARCHAR(50)	yes
`INGRESO`	DOUBLE(53)	no
`OPERADO`	BIT(1)	no
`NOTAS`	VARCHAR(100)	yes
`TRANSFERIDO`	BIT(1)	no

`TABLA RAMODOS`

Rows: 66 | Columns: 1

Column	Type	Nullable
`RAMO2`	VARCHAR(50)	no

`ban`

Rows: 1 | Columns: 1

Column	Type	Nullable
`banco`	VARCHAR(50)	no

Excluded tables

Table	Rows
`FECHAIF`	1
`INFORME`	0
`INFORME BA`	0

61 KiB Raw Blame History Unescape Escape

Legacy Database Reference

Why this file exists

The four files at a glance

How the three real databases relate to each other

Known data-quality issues and extraction quirks

Table exclusion rationale

Working with this without Windows

Appendix: full table catalog

UTILITIES.accdb

AGUA EVALUA

CHEQUE FM3

CLAVES

COBRO3

DATGRAL

DATMEX

DATOS FUTUROS

DIRECCION

DIRECCIONAWEB

EFECTIVO

EFECTIVO FM3

EFECTIVO_BACKUP

FECHAIF

FECHAS

FEE ANUAL

IVA 2015

LUZ EVALUA

LUZSCAN

MAIL

PARAPER

PROFILE

PROPANO

RECIBONOCLIENT

RPUN

SHCP 5

TEL EVALUA

TELEF

TIPO CAMBIO

TIPO HIST

TRUSTVENCE

TYPE OF TRX

datos2

datosfreak

datosfreak2

fee15

pagos email

pagos todos

Excluded tables

SEGUROS 16_be.mdb

AJUSTA

AJUSTADORES

AJUSTADORESATLAS

ATLAS

BENEF

COMENTARIOS

COMPAN

CONTACTS

DATGRAL

DATOS

DATOS AUTOS

DATOS AUTOS TIPO

EDOSEG

EFECTIVO

FECHAIF

FECHAS EDOSEG

FECHAS PRIMA NETA

FORMAS

IMPUESTOS

IMPUESTOS_AUTOS

INCENDIO

LICENCIAS

LIQUIDA SELLO

LIQUIDAAD

M EMPR

MCA2

MULT

RECIBONOCLIENT

TABLA AUTOS

TABLA AUTOS AMPL

TABLA AUTOS AMPL R

61 KiB

Raw Blame History

`AGUA EVALUA`

`CHEQUE FM3`

`CLAVES`

`COBRO3`

`DATGRAL`

`DATMEX`

`DATOS FUTUROS`

`DIRECCION`

`DIRECCIONAWEB`

`EFECTIVO`

`EFECTIVO FM3`

`EFECTIVO_BACKUP`

`FECHAIF`

`FECHAS`

`FEE ANUAL`

`IVA 2015`

`LUZ EVALUA`

`LUZSCAN`

`MAIL`

`PARAPER`

`PROFILE`

`PROPANO`

`RECIBONOCLIENT`

`RPUN`

`SHCP 5`

`TEL EVALUA`

`TELEF`

`TIPO CAMBIO`

`TIPO HIST`

`TRUSTVENCE`

`TYPE OF TRX`

`datos2`

`datosfreak`

`datosfreak2`

`fee15`

`pagos email`

`pagos todos`

`AJUSTA`

`AJUSTADORES`

`AJUSTADORESATLAS`

`ATLAS`

`BENEF`

`COMENTARIOS`

`COMPAN`

`CONTACTS`

`DATGRAL`

`DATOS`

`DATOS AUTOS`

`DATOS AUTOS TIPO`

`EDOSEG`

`EFECTIVO`

`FECHAIF`

`FECHAS EDOSEG`

`FECHAS PRIMA NETA`

`FORMAS`

`IMPUESTOS`

`IMPUESTOS_AUTOS`

`INCENDIO`

`LICENCIAS`

`LIQUIDA SELLO`

`LIQUIDAAD`

`M EMPR`

`MCA2`

`MULT`

`RECIBONOCLIENT`

`TABLA AUTOS`

`TABLA AUTOS AMPL`

`TABLA AUTOS AMPL R`

`TABLA AUTOS LIMIT`

`TABLA AUTOS RC R`

`TABLE DATOS LIQUIDA MCA2`

`TABLE DATOS LIQUIDA MF`

`TABLE DATOS LIQUIDA RES`

`TABLE DATOS LIQUIDA TUR`

`TIPOS`

`UTILSEG`

`gen1`

`gen2`

`DATOS E`