FRB_SR Database

Edit:  Microsoft has discontinued the DataMarket program.  We are working to re-establish this service.

Get It Now on Microsoft’s Azure DataMarket . . .

 

FRB_SR . . . All Federal Reserve Bank Statistical Data in One Place!

A great source of historical, research, and test data, the FRB_SR database consolidates the statistical releases published by the Federal Reserve Bank.  There are

  • 13 statistical releases
  • 35 Datasets
  • Over 15,000 Series
  • Over 8.7 million data points . . . going back to 31 Jan 1919!

No more manual downloads and processing XML files . . . FRB_SR is a fully functional database . . . the data are ready for use; the pic on this ad shows the data structure.

Includes:

Bank Assets & Liabilities
–Aggregate Reserves of Depository Institution and the Monetary Base (H.3)
–Assets and Liabilities of Commercial Banks in the U.S. (H.8)
–Charge-off and Delinquency Rates
–Senior Loan Officer Opinion Survey on Bank Lending Practices

Business Finance
–Commercial Paper
–Finance Companies (G.20)

Exchange Rates and International Data
–Foreign Exchange Rates (G.5 / H.10)

Flow of Funds Accounts
–Flow of Funds Accounts of the United States (Z.1)

Household Finance
–Consumer Credit (G.19)*
–Finance Companies (G.20)
–Household Debt Service and Financial Obligations Ratios (FOR)

Industrial Activity
–Industrial Production and Capacity Utilization (G.17)*

Interest Rates
–Selected Interest Rates (H.15)

Money Stock and Reserve Balances
–Aggregate Reserves of Depository Institution and the Monetary Base (H.3)
–Factors Affecting Reserve Balances (H.4.1)*

*Principal Economic Indicators

Data are current daily within 2 hours of release by the Federal Reserve Bank.
FRB_SR (data schema and structures) is the original work of, and is owned and copyrighted by the author.  Distribution and use of FRB_SR is under license; the author reserves all rights.  FRB_SR is expressly NOT in the public domain and remains the sole property of the copyright owner.  Distribution or modification of FRB_SR without the knowledge, review, and express permission of the copyright owner is strictly prohibited.  The Federal Reserve Bank statistical releases are public information.

Why pay for FREE DATA?! If you are a do-it-yourselfer or only need partial data, the data are freely available at the Federal Reserve Bank website.  The “Data Download” instructions are here.  Fee based custom development and support are available; please Contact Us.

Get It Now on Microsoft’s Azure DataMarket . . .

U.S. Bank Financial Condition and Performance Data Service

Edit:  Microsoft has discontinued the DataMarket program.  We are working to re-establish this service.

For Immediate Release 8:00 AM EST

10/17/2012

MacroTrenz Corp. Releases Its Latest Solution
U.S. Bank Financial Condition and Performance Data Service
On Microsoft’s Azure Data Marketplace

Jacksonville, FL — 10/17/2012 — MacroTrenz Corp. today announced the release of their U.S. Bank Financial Condition and Performance Data Service which returns, in a concise and readily usable data format, the regulatory reports, financial data, and structural information for FDIC-insured bank and thrift institutions published by the Federal Financial Institutions Examinations Council (FFIEC). The Windows Azure platform, Microsoft’s cloud services platform, provides MacroTrenz Corp. with the ability to build, manage, and deploy cloud based applications.

“With persistent uncertainty and even crisis in world finance, safety and soundness in the banking industry is under intense scrutiny. Our U.S. Bank Financial Condition and Performance Data Service on Microsoft’s Azure Data Marketplace helps financial professionals get the detailed bank condition and performance information they require. said Geary M. McIver, President of MacroTrenz Corp.

MacroTrenz Corp. automates critical data processes such as the U.S. Bank Financial
Condition and Performance Data Service
which provides easy search and data retrieval across the full set of over 350,000 quarterly Bank Call and Uniform Bank Performance reports representing over one billion data points. In addition, individual MDR element data can be retrieved across banks and reporting periods.

MacroTrenz Corp. data consulting services:

  • SQL Server Database Audits

  • SQL Server Database Conversions and Migrations

  • SQL Server Database Tuning and Optimization

  • SQL Server Database Reporting, Business Intelligence, and Analytics

More services information is available at our website.

Providing quality, innovation, and reliability for 17 years, MacroTrenz Corp. specializes in helping customers use and manage data.

#########

Product or service names mentioned herein are the trademarks of their respective owners.

For more information, press only, please contact us.

Federal Reserve Bank Data Service Debut

Edit:  Microsoft has discontinued the DataMarket program.  We are working to re-establish this service.

For Immediate Release 12:22 PM EST

12/15/2011

MacroTrenz Corp. Releases Its Latest Solution
Federal Reserve Bank Statistical Data Solution
On Microsoft’s Azure Data Marketplace

Jacksonville, FL — 12/15/2011 — MacroTrenz Corp. today announced the debut of their Federal Reserve Bank Statistical Data service on Microsoft’s Azure Data Marketplace. The service helps enable customers to research and retrieve Federal Reserve Bank Statistics, Historical Data, Surveys, and Reports across the full set of over 100,000 “SERIES” reports and over 8.7 million data points. Such comprehensive functionality is provided by neither the Federal Reserve Bank nor other data services. The Windows Azure platform, Microsoft’s cloud services platform, provides MacroTrenz Corp. with the ability to build, manage, and deploy cloud based applications.

“In today’s world financial climate, easy and ready access to critical Federal Reserve Bank data is more important than ever. Our Federal Reserve Bank Statistical Data service on Microsoft’s Azure Data Marketplace provides insight and access to the Fed’s current monetary policy goals as reflected by it’s key statistical data. said Geary M. McIver, President of MacroTrenz Corp.

MacroTrenz Corp. automates critical data processes such as Federal Reserve Bank Statistical Data which includes:

Bank Assets & Liabilities
–Aggregate Reserves of Depository Institution and the Monetary Base (H.3)
–Assets and Liabilities of Commercial Banks in the U.S. (H.8)
–Charge-off and Delinquency Rates
–Senior Loan Officer Opinion Survey on Bank Lending Practices

Business Finance
–Commercial Paper
–Finance Companies (G.20)

Exchange Rates and International Data
–Foreign Exchange Rates (G.5 / H.10)

Flow of Funds Accounts
–Flow of Funds Accounts of the United States (Z.1)

Household Finance
–Consumer Credit (G.19)*
–Finance Companies (G.20)
–Household Debt Service and Financial Obligations Ratios (FOR)

Industrial Activity
–Industrial Production and Capacity Utilization (G.17)*

Interest Rates
–Selected Interest Rates (H.15)

Money Stock and Reserve Balances
–Aggregate Reserves of Depository Institution and the Monetary Base (H.3)
–Factors Affecting Reserve Balances (H.4.1)*

Data are current daily within 1 hour of release by the Federal Reserve Bank.

MacroTrenz Corp. data consulting services:

  • SQL Server Database Audits

  • SQL Server Database Conversions and Migrations

  • SQL Server Database Tuning and Optimization

  • SQL Server Database Reporting, Business Intelligence, and Analytics

More services information is available at our website.

Providing quality, innovation, and reliability for 16 years, MacroTrenz Corp. specializes in helping customers use and manage data.

#########

Product or service names mentioned herein are the trademarks of their respective owners.

For more information, press only, please contact us.

Federal Reserve Bank Data


Federal Reserve Bank Statistical Data All in One Place!

Get It Now on Microsoft’s Azure DataMarket . . . Free Trial!

A great source of historical, research, and test data, the FRB_SR database consolidates the statistical releases published by the Federal Reserve Bank.  There are

  • 14 statistical releases
  • 39 Datasets
  • Over 15,000 Series
  • Over 8.7 million data points . . . going back to 31 Jan 1919!

No more manual downloads and processing XML files . . . FRB_SR is a fully functional database . . . the data are ready for use; the pic on this ad shows the data structure.

Includes:

Bank Assets & Liabilities
–Aggregate Reserves of Depository Institution and the Monetary Base (H.3)
–Assets and Liabilities of Commercial Banks in the U.S. (H.8)
–Charge-off and Delinquency Rates
–Senior Loan Officer Opinion Survey on Bank Lending Practices

Business Finance
–Commercial Paper
–Finance Companies (G.20)

Exchange Rates and International Data
–Foreign Exchange Rates (G.5 / H.10)

Flow of Funds Accounts
–Flow of Funds Accounts of the United States (Z.1)

Household Finance
–Consumer Credit (G.19)*
–Finance Companies (G.20)
–Household Debt Service and Financial Obligations Ratios (FOR)

Industrial Activity
–Industrial Production and Capacity Utilization (G.17)*

Interest Rates
–Selected Interest Rates (H.15)

Money Stock and Reserve Balances
–Aggregate Reserves of Depository Institution and the Monetary Base (H.3)
–Factors Affecting Reserve Balances (H.4.1)*

–Money Stock Measures (H.6)

*Principal Economic Indicators

Data are current daily normally within minutes of release by the Federal Reserve Bank.
FRB_SR (data schema and structures) is the original work of, and is owned and copyrighted by the author.  Distribution and use of FRB_SR is under license; the author reserves all rights.  FRB_SR is expressly NOT in the public domain and remains the sole property of the copyright owner.  Distribution or modification of FRB_SR without the knowledge, review, and express permission of the copyright owner is strictly prohibited.  The Federal Reserve Bank statistical releases are public information.

Why pay for FREE DATA?! If you are a do-it-yourselfer or only need partial data, the data are freely available at the Federal Reserve Bank website.  The “Data Download” instructions are here.  Fee based custom development and support are available; please Contact Us.

 

Get It Now on Microsoft’s Azure DataMarket . . . Free Trial!

 

 

U.S Bank Financial Condition and Performance Data Service


Your satisfaction is our number one priority.  Please contact us for support inquiries.

U.S Bank Financial Condition and Performance Data Service

Documentation

Contents

  1. Data Description
  2. Function Imports
  3. Entity Diagram

Data Description

The U.S Bank Financial Condition and Performance Data Service publishes, in a concise and readily usable data format, the regulatory reports, financial data, and structural information for FDIC-insured bank and thrift institutions published by the Federal Financial Institutions Examinations Council (FFIEC). The earliest data provided is from March 31, 2001. The U.S Bank Financial Condition and Performance Data Service provides data search and retrieval across the full set of over 350,000 quarterly Bank Call and Uniform Bank Performance reports representing over one billion data points. In addition, individual MDR element data can be retrieved across banks and reporting periods.

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Function Imports

      • [GET_REPORTING_PERIODS]:
        • Query Keys
          1. None.
        • Columns Returned . . .
          • PERIOD_ID
        • Use . . . Returns a list of all quarterly reporting period identifiers in the format YYYYMMDD.
        • Example URL Query: GET_REPORTING_PERIODS
      • [GET_BANK_LOOKUP]:
        • Query Keys
          1. “PERIOD_ID”, int, required . . . reporting period in the format YYYYMMDD.
          2. “SEARCH_SNIPPET”, string(10 characters max, alphanumeric only), required . . . searches for string in these bank information fields in this order:
            1. Name
            2. Address
            3. City
            4. State
            5. IDRSSD (FFIEC Bank Identifier)
            6. FDIC Certificate Number
            7. OCC Charter Number
            8. OTS Docket Number
            9. ABA Routing Number
            10. ZIP Code
        • Columns Returned . . .
          • PERIOD_ID . . . reporting period identifier
          • ID_RSSD . . . FFIEC bank identifier
          • FDICCertNumber . . . FDIC Certificate Number
          • OCCChartNumber . . . OCC Charter Number
          • OTSDockNumber . . . OTS Docket Number
          • PrimaryABARoutNumber . . . ABA Routing Number
          • Name . . . bank name
          • Address . . . bank address
          • City . . . bank city
          • State . . . bank state
          • ZIP . . . zip code
        • Use . . . identify individual bank/branch information and address(es) .
        • Example URL Queries:
          1. GET_BANK_LOOKUP?PERIOD_ID=20111231&SEARCH_SNIPPET=’hancock’
          2. GET_BANK_LOOKUP?PERIOD_ID=20111231&SEARCH_SNIPPET=’10057′
      • [GET_REPORT_CALL]:
        • Query Keys
          1. “ID_RSSD”, int, required.
          2. “PERIOD_ID”, int, required . . . reporting period in the format YYYYMMDD.
        • Columns Returned . . .
          • ID_RSSD . . . FFIEC bank identifier
          • REPORT_DATE . . . reporting period date
          • ENTRY . . . report line item, e.g. “section”, “subsection”, “blankline”, MDR element name
          • ENTRY_TYPE . . . report line item type, e.g. fact, credit, debit
          • ENTRY_PERIOD . . . report line item time span type, e.g. duration, instant, null for fact ENTRY_TYPE
          • ENTRY_STARTDATE . . . report line item time span start
          • ENTRY_ENDDATE . . . report line item time span end
          • UNIT_TYPE . . . classification of the report line item VALUE, e.g. USD
          • DECIMALS . . . number of decimal digits in the report line item VALUE
          • VALUE . . . the report line item datum
          • HEADER_LINE . . . the report line item description
          • HEADER_COLUMN . . . the report line item column description
          • SCHEDULE . . . report of condition or report of income schedule identifier
          • SCHEDULE_LINE . . . report of condition or report of income schedule line identifier
          • SCHEDULE_COL . . . report of condition or report of income column identifier
          • USE . . . the report line item usage requirement, e.g. required, optional
          • LEVEL . . . formatting information indicating the level of indentation for the report line
          • SORT . . . the report line item sort key
        • Use . . . returns the full CALL REPORT, in a concise and readily usable data format, for the specified bank and reporting period.
        • Example Query: GET_REPORT_CALL?ID_RSSD=37&PERIOD_ID=20111231
      • [GET_REPORT_UBPR]:
        • Query Keys
          1. “ID_RSSD”, int, required.
          2. “PERIOD_ID”, int, required . . . reporting period in the format YYYYMMDD.
        • Columns Returned . . .
          • ID_RSSD . . . FFIEC bank identifier
          • REPORT_DATE . . . reporting period date
          • REPORT_PAGE . . . report page name
          • REPORT_LINE . . . the report line item description
          • ENTRY . . . report line item, e.g. “section”, “subsection”, “page”, “blankline”, MDR element name
          • ENTRY_TYPE . . . report line item type, e.g. fact, credit, debit
          • ENTRY_PERIOD . . . report line item time span type, e.g. duration, instant, null for fact ENTRY_TYPE
          • ENTRY_STARTDATE . . . report line item time span start
          • ENTRY_ENDDATE . . . report line item time span end
          • UNIT_TYPE . . . classification of the report line item VALUE, e.g. USD
          • DECIMALS . . . number of decimal digits in the report line item VALUE
          • VALUE . . . the report line item datum
          • USE . . . the report line item usage requirement, e.g. required, optional
          • LEVEL . . . formatting information indicating the level of indentation for the report line
          • SORT . . . the report line item sort key
        • Use . . . returns the full UBPR REPORT, in a concise and readily usable data format, for the specified bank and reporting period.
        • Example Query: GET_REPORT_UBPR?ID_RSSD=37&PERIOD_ID=20111231
      • [GET_RAW_DATA]:
        • Query Keys . . . NOTE: while each query key is optional, at least one must must be specified to get results.
          1. “ID_RSSD”, int, optional.
          2. “PERIOD_ID”, int, optional . . . reporting period in the format YYYYMMDD.
          3. “ELEMENT_NAME”, string(8 characters max, alphanumeric only), optional.
        • Columns Returned . . .
          • ID_RSSD . . . FFIEC bank identifier
          • PERIOD_ID . . . reporting period date
          • ELEMENT_NAME . . . MDR element name, e.g. “RIAD4150”, “UBPRE001”
          • ENTRY_STARTDATE . . . report line item time span start
          • ENTRY_ENDDATE . . . report line item time span end
          • UNIT_TYPE . . . classification of the report line item VALUE, e.g. USD
          • DECIMALS . . . number of decimal digits in the report line item VALUE
          • VALUE . . . the report line item datum
        • Use . . . returns raw data in a concise and readily usable format.
        • Example URL Query using keys: GET_RAW_DATA?ID_RSSD=37&PERIOD_ID=20111231

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Entity Diagram

FFIEC Entity Diagram

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Copyright © 2011-2017, MacroTrenz Corp., All rights reserved.

Federal Reserve Bank Financial Data Service

Edit:  Microsoft has discontinued the DataMarket program.  We are working to re-establish this service.

Your satisfaction is our number one priority.  Please use the contact us for support inquiries.

Federal Reserve Bank Financial Data Service

Documentation

Contents

  1. Data Description
  2. Primary Entities
  3. Lookup Entities
  4. Entity Diagram

Data Description

The Federal Reserve Bank Financial Data Service is a concise and readily usable form of the Statistics, Historical Data, Surveys, and Reports published in flat file format by the U.S. Federal Reserve Bank.  The Federal Reserve Bank Financial Data Service provides data search and retrieval across the full set of over 100,000 “SERIES” reports and over 8.7 million data points. Such comprehensive functionality like this is not provided by the Federal Reserve Bank.

  • The hierarchy of the data has four levels.Statistical Release: Major divisions of financial and ecomomic information. | Data Sets: A grouping category wherein each Series uses the same attributes set. | Series: Equivalent to a “Report”, each with a unique set of values applied to the attributes. | Observations: “The Data” for a particular SERIES.
  • Each hierarchy level adds a respesentive key for that level.Statistical Release: respesentive key = SR_ID | Data Sets: respesentive key = DataSet_ID | Series: respesentive key = SERIES_ID | Observations: respesentive key = OBS_ID
  • Record sets at each level are identified by the parent keys in the hierarchy.Statistical Release: record set identifier = (N/A for this top level) | Data Sets: record set identifier = SR_ID | Series: record set identifier = SR_ID & DataSet_ID | Observations: record set identifier = SR_ID, DataSet_ID, & SERIES_ID
  • Unique records at each level are identified by ALL keys down through the hierarchy to that level.Statistical Release: unique record identifier = SR_ID | Data Sets: unique record identifier = SR_ID & DataSet_ID | Series: unique record identifier = SR_ID, DataSet_ID, & SERIES_ID | Observations: unique record identifier = SR_ID, DataSet_ID, SERIES_ID, & OBS_ID
  • Except for Series, there is only one OData Entity for each level. Due to the varying attribute sets among Series, the lookup table SERIES_ATTRIBUTES provides attribute details for a particular Series. The intended user interface is a drill down through the hierarchy to identify the key set SR_ID, DataSet_ID, & SERIES_ID to then query OBSERVATIONS for all observation rows for a SERIES. Users should be able to retrieve a unique record at any level in the hierarchy by also specifiying optional parameters for that entity. All result sets returned to the user should include all entity properties (columns).

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Primary Entities

  • [STATISTICAL_RELEASES]:

    Top level, lists details of each Statistical Release

    • Query Keys
      1. “SR_ID”, int, optional. . . noramlly not required, result set is small (12 rows currently)
    • Columns Returned . . .
      • SR_ID . . . key identifier
      • NAME
      • DESCRIPTION
      • DATE
    • Use . . . Primary purpose is to identify “SR_ID” for drilldown to DATASETS.
  • [DATASETS]:

    Second level, “label” for grouping SERIES having the same SERIES_ATTRIBUTES.

    • Query Keys
      1. “SR_ID”, int, optional . . . noramlly not required, result set is small (35 rows currently)
      2. “DataSet_ID”, int, optional . . . noramlly not required, result set is small (35 rows currently)
    • Columns Returned . . .
      • SR_ID . . . key identifier
      • DataSet_ID . . . key identifier
      • DATASET . . . identification abbreviation
      • DATASET_DESCRIPTION
      • SERIES_COUNT . . . number of series within the DATASET
    • Use . . . Primary purpose is to identify “SR_ID” and “DataSet_ID” for drilldown to SERIES. Take note of the SERIES_COUNT column.
  • [SERIES]:

    Third Level, lists details, e.g. SERIES_NAME, DESCRIPTION, etc.

    • Query Keys
      1. “SR_ID”, int, required.
      2. “DataSet_ID”, int, required.
      3. “SERIES_ID”, int, optional.
    • Columns Returned . . .
      • SR_ID . . . key identifier
      • DataSet_ID . . . key identifier
      • SERIES_ID . . . key identifier
      • DATASET . . . identification abbreviation
      • SERIES_NAME
      • DESCRIPTION
      • FREQUENCY . . . data observation frequency, e.g. daily, monthly, etc.
      • RECORD_COUNT . . . number of observations
    • Use . . . Primary purpose is to identify “SR_ID”, “DataSet_ID”, AND “SERIES_ID” for drilldown to OBSERVATIONS(the data).
  • [OBSERVATIONS]:

    Fourth Level, lists the actual data.

    • Query Keys
      1. “SR_ID”, int, required.
      2. “DataSet_ID”, int, required.
      3. “SERIES_ID”, int, required.
      4. “OBS_ID”, int, optional.
    • Columns Returned . . .
      • SR_ID . . . key identifier
      • DataSet_ID . . . key identifier
      • SERIES_ID . . . key identifier
      • OBS_ID . . . key identifier
      • OBS_STATUS . . . e.g. A (normal), NA (not available)
      • OBS_VALUE
      • TIME_PERIOD

      SR_ID, NAME, DESCRIPTION, DATE.

    • Use . . . pulls the actual data for a SERIES.

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Lookup Entities

  • [SERIES_ATTRIBUTES]:

    Third Level, lookup “Helper” table with SERIES specific attributes/value pairs.lists details, e.g. SERIES_NAME, DESCRIPTION, etc.

    • Query Keys
      1. “SR_ID”, int, required.
      2. “DataSet_ID”, int, required.
      3. “SERIES_ID”, int, required.
    • Columns Returned . . .
      • SR_ID . . . key identifier
      • DataSet_ID . . . key identifier
      • SERIES_ID . . . key identifier
      • ATTRIBUTE_ID . . . key identifer
      • ATTRIBUTE . . . e.g. UNIT_MULT
      • ATTRIBUTE_DESCRIPTION
      • ATTRIBUTE_VALUE . . . e.g. 1000000 (millions)
      • ATTRIBUTE_VALUE_DESCRIPTION
    • Use . . . Primary purpose is to identify a SERIES’ attributes, e.g. Series Name, Currency, Frequency code list, Loan type, etc.

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Entity Diagram

FRB_SR Entity Diagram

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Copyright © 2011-2017, MacroTrenz Corp., All rights reserved.

Database Consulting Services

Database Consulting Services . . . some plain talk.

SQL Server Database Audits

Do you have persistent data issues that never seem to get and STAY fixed?  Schema . . . the basic rules and building blocks of a database . . . is the single most important factor affecting database performance, reliability, accuracy, and security along with the capability to do reports and analysis to support business decisions and on-going operations.  A schema audit is perhaps the most cost effective way to identify long term problems and get them resolved once and for all.  An independent and unbiased audit, done collaboratively with your staff, brings consensus among IT factions on issues and sets the focus on an achievable solution.

SQL Server Database Conversions and Migrations

Second chances are few . . . but upgrading to a full scale database management system is an opportunity to “get it right”.  If your data needs have out grown small scale spreadsheet and data programs (e.g. Excel and Access), the conversion and migration process is your chance to help set a positive course for your business.  Make it a priority, and your data system will be responsive and flexible to present and future business needs.  Neglecting this opportunity is usually an “ongoing failure” producing problem after problem over time and can negatively impact your business for years.

SQL Server Database Tuning and Optimization

Regular tuning and optimization is a routine and continuous requirement as both the nature and amount of data change.  If you don’t have staff performing this duty, it should be done at the first sign of performance issues and a periodic maintenance schedule established.  Automated maintenance routines will help keep things in order in between.  Deferred maintenance certainly becomes more expensive to remediate.

SQL Server Database Reporting, Business Intelligence, and Analytics

Not getting the information and answers you need in a timely and cost effective manner?  Over the years the data business has become segmented and highly specialized.  As data professionals have narrowed their focus to a limited or even a single subject matter, the data effort has become decentralized and fragmented.  The database world now has administrators, developers, architects, modelers, report builders, and business intelligence analyst . . . not to mention the systems engineers who do the database software installs but know nothing about the data world.  All having their own objectives and priorities.  This is especially important to reporting, BI and analytics because their functions are downstream of everything else.  Yet, few of these specialist have the knowledge and skills to fully comprehend and follow the process upstream when issues arise.  They report the problem and wait for it to work it’s way through the bureaucracy.  Priorities are usually set by the process of escalation to and involvement of higher management.  The key to their effectiveness is to have someone who can develop and bring an integrated view of the data process from beginning to end.

 

Please let me know how I can be of service to you.