The need to sharing information among business partners has existed long before computers. 

Creating assets take time.  One organization I  worked with had built  an asset coordinating data from dozens of agencies  in  response  to  a  natural  disaster.  It  was put together  on  the  fly  and was a  resounding  success.  The problem was that  the  solution was not  sustainable.  It was a one off based on personal relationships even though its value has many  other uses.  

 It has always been  that the  better informed, the better the decision.  Informed is based on the  critical difference between data and information.  Have you  ever had too much  data  and no information?  Information is data in context.  Just adding data  sources without translating  them into what that  means to the enterprise adds no value.  

Creating  information is  not  simple. It has been the  bulk-load  of  work  for over 30 years since the  inception of  data warehousing and its  descendants.  Cleansing data and  relating data are still the  majority of  work.  It is  one of the  primary  hurdles  for  AI implementations  today.  (It does seem incomprehensible that after three  decades we still  have the same issues  with data quality in systems).

The need to create and curate  information  is  critical to future success.  The industry has responded with  vendor driven techniques  like  IPaaS (Integration Platfrom  as  a  Service).  BAaaS is a similar concept but attempts to simplify  all integrations, security, tracking, and asset creation.

Organizations have long responded to demand for sharing data with  point products (API management, secure file  transfer, etc.).  BAaaS attempts to  resolve this complexity with a layer of capabilities that enforce  preferred implementations.  It requires a single store front for assets (ATLaaS is the model).  Assets get categorized by name, type of asset, scope of exposure, description  to facilitate discovery, owner, simplified classification, subscription policy,  provenance, and access requirements.  The classification determines the implementation.  For data files this could range from a "dropbox" implementation for  non-secured  files to a high cost, high volume, encrypted  file transfer solution.  The goal is to implement appropriate access based on cost and risk.  The plumbing should be similarly standardized. 

Approval processes as standardized with owner acceptance of requests.  Standardization is  critical for  support and long term replacement (new pipes).  One organization had a proven savings of over $1M/year software maintenance and significant operation  savings.  

Operationally  BAaaS offers constant, consistent monitoring.  Standardization not  only simplifies support, but  it  lends itself to optimization.  It simplifies the monitoring by AI bots who can proactively resolve problems, note access anomalies, and tune the  solution.

Transparency is  a must discussed concept.  ATLaaS tried to resolve this  by adding context to access.  BAaaS offers another needed road to openness. 

I  was part of the team (a small part) of  the  team that delivered  a state's Open Data solution.   My part of the solution was to implement a way  for participants (agencies, localities, partners)  to deliver files for upload to the solution.  An early  self-provisioning solution (based on earlier versions  of  BAaaS and ATLaas) was implemented within six weeks to allow over 100 participants.  The first implementation had tens of thousands of files.  What was interesting wasn't the agility and delivery  times, but what an Open Data solution offered.  It offered any  constituent access to the  data.  Not simply  as a file, but  with many  integration capabilities APIs, a SQL, interface, etc.  The interfaces allowed easy access and supported hackathons nationwide.  The enterprise question is why  can't this  concept be applied to every  file we share?  

This is one feature of BAaaS.  Every file that  is shared is an asset that can be leveraged.  It can be shared with other partners and internal  information practitioners.  It now support the integration tools and hackathons.  The data now requires more security, but  that comes with registering the asset.  The new integration techniques have the  same owner and standard acquisition processes. They  all get  tracked  in BAaaS.  

Since the files  are delivered in a standardized format (there may  be several), common agents  can turn  them into any  desirable  format that the enterprise  values (JSON, Tableau).   For legacy  systems, their file  shares  can be leveraged as a transition  to capability end-state.  Additionally, access to these assets can be used  to understand information needs for the  organization (inlcuding AI).

BAaaS offers an opportunity  to attack the  darkest shadows.  Spreadsheets run  a good  deal of an organization.  What if we can take  a  spreadsheet, persist it, and generate new assets from it?  This could mean the spreadsheet could be integrated into  processes and tools.  They  would be curated by  the  owner and published as needed.  

BAaaS becomes the  consolidated store front for asset  sharing.  These assets are not always  shared today.  Business events, feeds,  and UI objects are powerful  assets that should  be leveraged.  Internal AI bots  are an asset that  can be leveraged  by general consumer  bots  (Gemini, CoPilot) and partners.  BAaaS establishes a consistent way  of  offering, approving, monitoring, and optimizing all these assets.  

BAaaS provides AI with many  opportunities.  A bot can operationally monitor and optimize  any  BAaaS solution.   AI can leverage BAaaS to evaluate  and create assets.  AI can leverage assets from BAaaS to create new tools (pages are example of UI objects)  and processes.  The next step in AI assisted coding is in common consumption patterns (tools).  

The goal behind all transformations  is a division of work and empowerment.  Giving  leaders and experts avenues to dynamically  influence the  enterprise.  

BAaaS is an opportunity for engagement.  It offers a consumer the  opportunity to find, create, use, and monitor assets.  

BAaaS supports a  much  needed analytics  and AI pipeline.  An analytics  pipeline is tied  to your  internal analytics  SDLC.  How do you test?  Who gets to test?  How does that  test get exposed as an asset (AI assets may  be the tool (AI bot) or  AI capability to be integrated  into  a  tool or process).  How does  the asset get  tested and promoted  into production?  How  is it monitored?  How  to do this safely  and securely?  

Although enterprise  SDLCs  vary, BAaaS can support the  ever changing  needs.  With the  explosion of AI projects how  do you create appropriate sandbox environments for  controlled  development?  In simplest form the AI/analytics "life cycle" includes discovery, exploration, test, pilot, and production.  Discovery  and exploration may be the  same, but the  goal is support multiple  initiatives.  These  environments may be by  unit  and individual.  In BAaaS to leverage an asset a "developer" would have to acquire a resource.  Even if this is a new external  data source, the unit bringing  in that  resource  will register  in BAaaS (and become owner and  establish usage  policies).  BAaaS will then allow  them to import  it  into  their test bed environment.  Imported assets into  a test bed can be  shared, but  test bed developed  assets are usually private until  promotion.  Promotion to another environment may change security.  For example a developer using an API may  use his own credentials, but on promotion a credential  for an application or  organization may  be required.

BAaaS users  follow self-service ATLaaS organizational provisioning.  Internal test beds  and external developer zones follow  the  same policies.

All this  expands what  hackathons  support.  From data that is  considered open, to having the  ability  to add context.  Assets created through  these pipelines become derived assets  with BAaaS (there is a concern over potential  for  unlntended disclosure).

Business is not technology focused.  BAaaS Supporting Products can change easily (underlying plumbing).  Set up preferred pipes depending on business need.  Standardization of plumbing (based  on asset  categorization) allows  for easy transition to different  technologies.  Standardization of  importing and transforming  assets follows the same pattern.  New assets can be formed or replaced with little  effort.  

The goal is to empower  the  business with the proven assets it requires.