Monday, November 22, 2021

Mom is Back with Her True Loves

 Carol E Sinur went to be with her beloved Lord, husband, and family on November 17, 2021, at the age of 94. While mom was legally blind, had hearing troubles, and short-term memory issues, she was still making friends and singing hymns to the workers at the nursing home. Mom was beautiful inside and out and lived out her priorities with great enthusiasm. She loved her Lord and sang about him, so I expect her in the heavenly choir. She loved my dad who passed on in May 2017 and she spent seven months here in Phoenix trying a new location. She wanted to finish out her time in the beloved home on the lake in northern Wisconsin because dad loved it. She wanted independence overall, so we surrounded her with the best visiting nurse in Julie and handyman Dean. She loved her friends at her local church and lived to go every Sunday she could. After battling COVID once, Pneumonia twice, and early sepsis three times, her body finally gave out. She was such a patient and loving person. Many will remember her humble life and the lessons she taught with her loving actions. Mom's hobbies were gardening, bird watching, painting by number, and completing puzzles until her sight left her. Here are some pictures of mom for your viewing pleasure.  

Mom in Her Early Years



Mom Loved Her Man



Mom Loved Her Family









Mom Loved Animals and the North Woods




Mom Loved Going to Church to Worship


Mom Was and Still is an Angel


Memorial Service 

Date December 3rd, 2021 Time 12 Noon  

Krause Funeral Home

9000 W. Capitol Dr

Milwaukee, WI 53222


Others Who Have Passed

Dad

Andy

Beth



Tuesday, November 16, 2021

The Rise of the Unified Database

We are living in the days of ever-expanding data sprawl caused by many hard to control factors. Data sizes are monstrous, the speed of data ingestion is ever increasing, the demand for better latencies is insatiable, and the complexity of the data is increasing. All of this while the need for custom views accessing the same information is exploding.

There are almost too many options that require specialized technical skills to create complex integrations that produce performance bottlenecks when working. It becomes even more nightmarish when testing and troubleshooting. Is the problem hopeless for organizations trying to manage and utilize their data? The answer lies in unified data and unified databases. Let's dig a bit into unified databases and how they relate to the holy grail of an effective data mesh.



What is Unified Data/Database?


A unified data model is a crucial piece to simpler data architecture and supports the data mesh. A unified data model offers an opportunity for organizations to analyze and operate on data from multiple sources in the context of shared views supporting shared business initiatives. The unified data model bridges different ecosystems, allowing organizations to contextualize data sources across various services. The task is statically or dynamically mapping each dataset to a more singular schema or view.

The Benefits of Unified Data/Databases

The benefit of data unification is that it provides a more holistic and accurate view of your many data sources while operating on them in different modes with different performance characteristics. The unified database can simplify the multiple tool and database environment and create a common denominator for data use without worrying about the scale. Unified databases can make data more practical and actionable while helping the data accuracy with the least energy by users and the data architecture keepers.

Downsides of Todays Data Architectures

Today organizations most often run-on specialty databases that have to be synchronized periodically. With the demand for more real-time management, this becomes a copy carousel that gets in the way. It leads to high-latency data makes always-on systems a nightmare. Because different data sources on different data architectures will require redundant transformation logic during the copying and transformation processes, often it isn't easy to guarantee consistency. It also becomes a challenge for data security and privacy programs. What's worse is that some of these copy/transformation processes fail, creating cascading delays and errors. Because our databases do specialized work enumerated below, the copying process is a never-ending nightmare. A unified database that can nearly do all the work of these specialized databases makes for a simpler world.

Generalized Databases

Typically generalized databases are for analytical purposes and rarely scale for transactional purposes. They are often easy to use and handle lower scales of data. Unfortunately, the complex uses and monster data tend to bog these analytically focused generalized databases.

Transactional Databases


Typically, transactional databases are focused on high-end operations where volume and efficiency are often desired. They can stand up to volumes generated by nano-second demands and work well in long logical work units for tasks and processes. However, they aren't for end users who often desire analytical feats leveraging siloed operational data where lateral views are not easily supported.

Analytical Databases

These databases are perfect for high-end analytical work where many sources are mainly focused on reading data but not necessarily creation, updates, or cascading deletes. However, they aren't as easy to use as generalized databases, so they are their own breed

Net; Net:

The unified database does a great job of spanning all these specialized databases. It often ends up as a hub through which many divergent views are connected to many divergent data sources of various types. It simplifies work and gets organizations off the copy carousel. The Unified database is an obvious choice as an infrastructural centerpiece for an organization's data mesh. It makes the shift from inflexible centralized data infrastructures to a data mesh that supports distributed “data-as-a-product” This is particularly important with a distributed data mesh that spans the clouds and on-prem.



Additional Reading:

Get Ready for the Big Shift to the Data Mesh

Convergent Data is Here to Stay

Real-Time Data Mixes Well with Archival Data Now

Leveraging Hybrid Cloud & Multi-Cloud

Speed, Scale & Agility Delivered with Distributed Joins

What’s Driving Data-Intensive Applications?

Reducing Data Sprawl

Wednesday, November 10, 2021

Attaining Autopilot Management

There are areas where automation is scary but necessary. It is true of management and driving vehicles. Both are on the way to more automation. We are seeing a revolution in driverless cars that is taking the driving tasks from the drivers and slowly passing them on to forms of automation combined with AI that learns effectively in real-time. This automation journey is bearing fruit now with driver-less taxis and driver-less freight hauling. The maturity of automated freight movement is taking off rapidly right now. Automation may just assist us in the nick of time with messed-up supply chains and driver shortages. There is an emerging parallel for managing organizations that is early and also taking off. There is a maturity to this autopilot management journey that I will try to convey here. Much of this revolves around making better decisions and taking appropriate actions speedily. This post will investigate the progress towards "Autopilot Management" and when we might see it. This post is building off some earlier posts on management by wire and the management cockpit.




What is Autopilot Management?

Autopilot management automates the management processes that observe, decide, act and watch for the expected or unexpected outcomes. It will not happen overnight and will evolve from simple automation to highly informed and interactive automatons. The quest for 100% automation might be a pipe dream. Still, great leaps of progress can be expected over the next few decades making business agility a powerful ally in the competition game. It is now possible because of the leaps in digital technologies, including AI that learns and postulates alternative courses at the strategic level, alternative rules at the tactical level, and focused actions at the operational level. The definition will have levels of maturity that I have described below.

Level 1 Notify:

Notification is the lowest level of automation. Events, patterns, and actions are aggregated and visualized, focused on known decision points. The management cockpit plays a key role here for integrated visualization. Automation will notify the manager(s) of abnormal or out-of-bounds conditions or situations. It is purely advisory and will grow to identify emergent events and patterns to sense potential emergent conditions related to threats and opportunities.

Level 2 Suggest:

Moving up the autopilot maturity curve, the management cockpit will provide/suggest alternative decisions and actions. In some cases, the management cockpit will suggest further analysis and collaboration to deal with expected or unexpected situations. It may be as simple as continuous improvement suggestions at the operational level or an adjustment of rules and boundaries for customer experiences or processes at the tactical level. However, it could draw attention to a potential shift in strategic direction or identify new opportunities and threats.

Level 3 Decide & Advise:

Kicking the intelligence factor up a notch to decide and offer alternative actions for automated action before action is taken. The best decision that automation is capable of is taken, but the manager still determines the proper course of action. In this case, the manager would still have the finals say to the measures necessary in the situation detected or emerging.

Level 4 Decide, Act & Offer Overrides:

Here the level of freedom the automation is given has increased. It decides, but it will take action if an override is not selected within a reasonable time frame. A manager had better have a solid reason not to take the intelligence's advice in the automation tested and established. It might really be necessary for an emergent condition that might need further analysis, particularly at the strategic level.

Level 5 Full Autopilot Management:

It is where the automation would not require a manager's attention to the dynamic management conditions. Instead, the automation would be free to do anything an experienced manager could do within boundaries and constraints preestablished. Finally, it is where the law, ethics, and corporate charter play a significant role.

Net; Net:

Since flexibility and responsiveness now rule the marketplace for today's successful organizations, autopilot management has and will continue to become an increasing focus for organizations. Remember that any organization might only apply total autopilot to selected problem domains and give less freedom to other problem domains. The amount of change and emergence we have seen and will continue to see is going to accelerate. Just look at the impact on our interconnected world that COVID has had so far. While we are early in the automation of management, we can expect much more as managers become more comfortable with the automation of their internal tasks for managing their domain. Also, managers will look to automate interactions with external environments and the traditional other internal domains.

Please Help with A Survey On Management Cockpits by Clicking Here You will receive a summary of the results if you leave an email address in February. Please be patient with the initial screen and use your down arrow on the drop-down selections.

Additional Reading:

Frictionless Management

Real-Time Fast Boards

Management Cockpits

Real-Time Strategy

Management by Wire





Tuesday, October 26, 2021

Art for the 3rd Quarter 2021

 Another creative quarter has past and the works keep coming. This time I did a fun one that tried a method that employed painter's tape and layers. Hope you get entertained with these pieces :)  If you want to see the rest of my collection, click here.



Costa Hummingbird


Yikes Stripes 



Tornado 



Crab Attack 


UFO


If you see something here or in my collection that stirs you, send me an email at jim.sinur@gmail.com. 


Tuesday, October 19, 2021

What are People Reading in 2021?

 We have three-quarters completed in 2021 and people are shifting their topics of interest. Here is a visualization of the activity on my blog. The trends are shifting based on readers' interests. Jumping to the number one issue is Results Oriented Communications in the age of Hybrid Work. While Customer Journeys are still of interest, they slipped to the number two issue. The next highest topic of interest is Management Visibility represented by the Management Cockpit and Real-Time Fast Boards. The next trend revolves around just what is Digital Transformation and where to put Digital Investments. The last in the top five trends revolve around Data Sprawl and Data Fabrics.  If you think there are other high-priority topics, you can put a comment on this post or hit me up on Linkedin. Below is a graphic depicting the activity for the last 12 months.


There is an interesting trend in offshore interests. Northern and Eastern Europe activity is on a marked increase for the year. The Nordic countries tend to be on the leading edge along with Germany. See the activity by a specific country other than the US & Russia below.


Looking at the last 6 months the digital investment topics seem to be on the rise.  


Net; Net:

I'm thankful for my loyal readership and would love any feedback you have on my analysis or ideas for new blogs. The activity is headed towards 800K in 2022 cumulative since mid-2013.  


Wednesday, October 13, 2021

Data Infrastructure Debt is Hampering Business Returns

There is a great deal of effort and cost associated with keeping technological components up to date and easy to use for more organizational leverage. Some folks estimate that this can reach near 90% of the budget allocated for technology. Every time we add another technological component, the more debt an organization builds. It is excruciating for data infrastructures as data can be used repeatedly to leverage business benefits. It gets in the way of delivering the newly desired outcomes of better customer journeys, more automation for cost savings, and leveraging an organization's resources in new and innovative ways. This post will concentrate on the data infrastructure portion of the technical dept. At the same time, it explores the causes, adverse effects, and how to solve them for data infrastructures and the ever-growing data sprawl.



Data Infrastructure Debt Causes

  •        An industry trend implies that modern applications need to be built on top of one or more special-purpose databases, thus adding more technical debt for each database. What makes this particularly difficult when combining and translating data for more use and leverage.
  •        Over the past decade, applications have become more data-hungry themselves. As a result, they require particular data dynamics, analytics, and models, implying more cross-use of existing data and new and unique databases.
  •         The explosion of free software tempts folks to leverage what software is already there, leading to more unique data infrastructure components. As a result, it creates a specialty database explosion.

Effects of Data Infrastructure Debt

  •         Data infrastructure debt is insidious and accumulates fast, and is very difficult to undo. It is a multiplier to the existing debt dragging back initiatives that organizations want.
  •         Initiatives that are given the green light are slowed down by the need to aggregate and translate data from many more sources than it would typically take. 
  •        Data infrastructure debt keeps the CIO on the sidelines instead of in the critical driver seat for digital efforts in the future. When the CIO is fighting a cost war instead of a results war, digital efforts wane in priority. 
  •         We have to hire all the specialty skills to keep the variety of special purpose and legacy databases.
  •         The drag causes businesses to set up their own technology efforts. But, unfortunately, they are often na├»ve to the problems they are creating and throw the debt over the fence to the CIO after making decisions the CIO would not have allowed.

How to Start Solving Data Debt?       

  •         It is essential to stop on-boarding new databases even though the software that comes with the new data might be free or low-cost. 
  •         Assuming organizations do not want to rip and replace databases immediately but slowly retire many, buying a modern DBMS that works well in the cloud as a No-SQL approach while still supporting SQL commands and databases is ideal.
  •         It is not by giving up on innovations and digital transformation efforts by prioritizing these great business outcome efforts overpaying past technical debt. However, it may mean not taking advantage of new features on old databases.

Net; Net:

Smart CIOs are reaching for single modern, scalable relational databases that can support the many needs of applications. It would include mixing real-time data with operational, warehouse, big, and archive data with ease. These databases can operate across cloud providers and on-premises. There is a big trend towards capable databases that can act as a data mesh while reducing the data infrastructure technical debt that promotes unnecessary data sprawl and the difficulties with protecting and leveraging that same data.



Tuesday, October 5, 2021

Management By Wire is just Around the Corner.

Management by wire has been the wish of many organizations starting back in the 1990s after the first practical application of fly by wire was delivered by Airbus in the late 1980s. The notion of giving management assists in holistically managing their organizations with software assists for single-loop learning situations grew fast. The parallel was evident and desirable, but until recently, it has not been delivered uniformly. This post will investigate the progress towards "management by wire" and when we will see it. 



                               Figure 1 Feedback Driven Learning Loop Approaches

What is Management by Wire?

Management by wire is a strategy in which managers rely on the organization's "information representation" and feedback loops (see Figure 1) generated by software and data working together to inform management of progress towards goals and outcomes while sensing any potential shift in conditions in and around that organization. It borrows from the idea of managing an airplane under various states and conditions while heading to a destination safely. It allows managers to not just "follow their gut feelings and experience" but provide detailed information for status and change for potential actions in a shortened time window. Because organizations are complex like airplanes, many measures are coming at the managers with different velocities and combinations that may be beyond a manager's capability at any one moment in time because of the breadth and depth of their responsibilities for managing goals, initiatives, and outcomes. 

Why are the Stars Aligning for it Now?

Digital technologies are giving us so much more capability than we had in the past. Here are some of the trends that point to attaining management by wire sooner than expected.

Better Visibility

We now have fast boards available to replace slow and lethargic dashboards where speed counts. Fast boards give managers up to the second views into essential issues. We now have management cockpits that can give integrated views of performance, states of crucial processes, and the success of any automation applied for better optimization.

Better Insights

With the help of better-integrated visibility, the manager can be equipped to leverage their experiences and gut feeling while surrounding them with additional analytical & AI assist combinations that I like to call poly-analytics. It can allow the managers to try different options before deciding and acting. It would be true for real-time operational adjustments all the way through to strategy adjustments.

A Better Data Mesh

Because data is getting easier to access with better integrations, dynamic transformations, and not having to worry about location, any manager can get the view they need to manage. While there are still challenges with data quality, the fly-by-wire notion will identify the priority projects for more data cleansing.

When Will Management by Wire Arrive?

Organizations are gaining experience with the building blocks for creating a manage by wire environment. There has been significant progress in managing data better logically as well in various physical locations. Because the management cockpit focuses on the crucial outcomes, data that feeds the cockpit gets better quicker. Integrated visualizations that leverage fast boards are growing by leaps and bounds. I expect organizations will have examples of portions of their business operating using management by wire principles by the end of this year and complete end-to-end business leverage of fly by wire in the next few years. Better get started soon or get left in the dust.

Net; Net: 

Since flexibility and responsiveness now rule the marketplace, today's successful organizations focus on sensing, orienting, deciding, and responding to the immediate need for change. Change necessary to be ready for new customer needs and shifting business environmental needs. Our world is now emergent in nature, so we need new approaches powered by better information technology that assists management in giving a holistic and integrated view of their organizations to start—inevitably leading to better interpretation of feedback information, better decisions, and improved actions. Even if we live in a steady-state world, optimizing organizations' responses will pay back handsomely.

 

Additional Reading:

Frictionless Management

Fast Boards

Management Cockpits

Real-Time Strategy