The Database of Now is About Leveraging Business Moments

 Recently I have been writing about the Database of Now without really defining it. While the definition was somewhat implied in the context of the write-ups, it is time to make it an official thing by defining it. Keep in mind that the definition is ideal at the moment and will emerge over time as digital technology advances to enable it. I have invited a coauthor who has some real-world examples to help flesh out this definition in context. Please welcome Dominic Ravita, whose bio is included.

Database of Now Definition

The Database of Now is a set of structured or unstructured data representing the present time or a moment without any processing or location delays. The Database of Now represents the most accurate and up to date state from which to make observations, decisions and take appropriate actions within the context of desired outcomes and goals.

The Database of Now must be considered in context and time continuums as the data meaning will vary with these vectors. An accurate state of now is a must to interpret the past and potentially predict the picture in emergent situations. Maintaining an accurate database of now is exceptionally challenging today with the amount and speed of data currently.

Benefits of the Database of Now

The Database of Now delivers operational insights and advantages by providing the current state of the business. It is a modern, efficient approach to cloud data management which broadens, accelerates and simplifies access to all the relevant in-the-moment with historical data while unifying data access styles and patterns

Why Care About the Database of Now? 

Digital transformation projects have accelerated to meet the increased demand for digital products and services, providing answers or solutions with immediacy. With the onset of the "always-on" culture, the pervasive use of smartphones and ubiquitous devices has driven a global shift in customer experience and consumer expectations. Business is now won or lost in a moment.

The Database of Now delivers the operational insights and advantages by providing the current state of business to proactively identify, capture, and capitalize on the most crucial moments for their endeavors and their customers' success. It achieves this by simplifying the data infrastructure required to execute diverse workloads across various data styles, patterns, and types. Data professionals, application stakeholders, and end-users gain the advantages of speed, scale, and simplicity.

Characteristics of the Database of Now

Instant Integration & transformation

Self-Managed with Incremental Ingestion/Cleaning

Run Anywhere Dynamically

Pattern & Event Recognition

Ability to Learn from Analytics, Machine Learning, and AI

Ability to Suggest Alternatives 

Ability to Take Action within Allowed Freedom Levels

Real-World Needs/Examples

 Cash Burn & Flow Need the Database of Now

Managing cash flow and burn down in uncertain times requires a “hands-on” real-time look at the monies and where they are going. Having a pulse on money and how much is flowing out right now is vital when unpredictable revenues. Having a chokehold on expenses can be just as much of a mistake today, so watching the corporate performance in real-time is a fantastic advantage. Watching spending patterns in the market and your organization in a real-time fashion is a key to organizational success. All of this monetary care must be watched in the context of current business scenarios that could be subtly changing and appearing in new events and patterns.

The Digital Customer Experience Needs the Database of Now

Measuring what your customer is experiencing in real-time yields much better satisfaction and results than looking at slanted surveys and inconsistently timed customer forums. Real-time data mining leveraging the Database of Now will give insights into customer behavior. While customers generally have consistent goals in the way they behave, they are now experiencing new pressures. Many organizations are declaring victory because they could continue supporting customers with a remote workforce quickly, but few look at the customer experience impact of the recent moves. The long term future of many organizations hangs in the balance with the customer experience. Digital, along with instant adaptation, will go beyond remote workers to customers and other partners.

Saving Lives Needs the Database of Now:

Seconds can save lives too. True Digital of Thailand's mission is to protect children from sex trafficking, and they do that by continuously processing massive amounts of web data to identify children in danger. They were able to decrease law enforcement investigation time by as much as 63%. True Digital also seeks to proactively reduce the likelihood of new viral hotspots, including COVID 19, by monitoring mass population movement trends and rates of population density changes through anonymized cellphone data location data.

Industry 4.0 Needs the Database of Now

When organizations interact to create outcomes with each other, especially when hyper-automation is involved, having instant transparency and acting nearest to the emergent events or patterns is essential. The Database of Now operates well at the edge, leveraging cloud presence, and work shifting capabilities. Measuring results at the edge and adapting within a set of guidelines and goals set up by inter-organizational governance bodies is essential for success.

Each of these examples has make-or-break moments in time. “Now Scenarios” are time-critical, but the length of time available for effective action varies by situation, as does the variety, volume, and velocity of data required. What is essential for these “Now Scenarios” is to leverage all the relevant data to establish the most accurate, complete, and timely context to drive proactive responses. For business operations and management, real-time revenue is lost or gained in a split second with each passing moment. 

Net; Net:

The new world is much faster in terms of reactive, proactive, or predictive decisions or actions. The Database of Now is now or will be a critical fundamental contributor to many digital transformation efforts. Organizations that can sense shifts and intercept the outcomes in time will be those who flourish best.

Additional Case Studies Can Be Found Here:

https://www.memsql.com/

Domenic Ravita is MemSQL’s Field Chief Technology Officer and Head of Product Marketing. He brings 24 years of experience across consulting, software development, architecture, and solution engineering leadership. He brings product knowledge and a senior technical perspective to field teams and to customers, and represents the voice of the customer to the product & engineering organization. He is a trusted technical and business advisor to the Fortune 500 having served global customers through multi-year transformations enabled by event-driven architectures. He has experience in distributed, in-memory data grids, streaming analytics, databases, integration, and data science.

Additional Reading on Database of Now:

Better Corporate Performance

https://jimsinur.blogspot.com/2020/08/increasing-corporate-performance-with.html

Accelerated Decisions

https://jimsinur.blogspot.com/2020/08/acceleration-of-decisions-helped-by.html

Contextual Intelligence

https://jimsinur.blogspot.com/2020/07/context-connecting-clues-for-data.html

Better Customer Experiences

https://jimsinur.blogspot.com/2017/09/do-you-need-technology-to-assist.html

Smart Data

https://jimsinur.blogspot.com/2020/07/is-your-data-smart-enough.html

 

 

Is Chasing Perfect Data a Reasonable Quest?

We have heard many quotes about the poor quality of data. In fact, there are those that want perfect data before they make a decision, Is that a realistic attitude towards data quality? While in some situations where data that is nearly perfect is an absolute must, there are other situations where you make the best decision under the circumstances. Let's Explore some of the issues a bit more.

Figure 1 Interaction of Data Quality and Decisions. 

What is Data Quality?

Gartner defines quality this way:

"The term "data quality" relates to the processes and technologies for identifying, understanding, and correcting data that support effective data and analytics governance across operational business processes and decision making. The packaged solutions available include a range of critical functions, such as profiling, parsing, standardization, cleansing, matching, enrichment, monitoring, and collaborating. 

I'd like to add my analysis to this solid base by referring to Figure 1 above that tries to show the interaction of time, decisions, and data. Looking at the X-axis we see the data quality increasing as efforts to make it better move it to a more clean, concise, and crisp state. The Y-axis represents a time continuum that goes from right this instant to all the time ever needed. Given all the time and all the money necessary, data can approach or even attain perfection until entropy enters into the equation. 

When data is new or first brought into an organization it is good for emergent and morphing sets of problems that are often under pressure to make decisions and even take actions on those decisions. Things are fuzzier at this point and a precise answer is often not possible, but progress can be made even with data of less quality. Often the decisions needed are not fully understood at this point in time. 

As the decisions become more known and even routine, the priority of the crucial decisions, goals, and outcomes tend to sort themselves out. This helps identify the critical data sources that need attention and efforts to get better over time. Some decisions become so important that operational excellence and customer interaction drive the need to make the decisions excellent too. This excellence demands more prefect data in most instances. 

When is Perfect Data Needed? 

Circumstances that Demand Perfect Data

When it comes to safety and the lives of people, it is hard to argue against perfect data, The problem occurs when the timing of getting that data perfect flies in the face of a need to make a decision to avoid downstream negative consequences. Sometimes decisions have to be made with less than perfect data. There are two strong forces pushing here that have to be balanced within the context of emergent or known scenarios.

Good Enough Data Sometimes Works

While it is easy to demand perfect data in order to make decisions and take action, sometimes real leadership finds good enough data to move forward. There is a danger to rely on just gut feel, so leveraging the data the best way possible considering its flaws is sometimes the best road taken. Sometimes additional scenario simulation is the answer. Sometimes some quick and dirty approaches to incremental data bolstering make sense. It may mean that you look at other similar decisions and data for insight.   

Net; Net: 

While we all chase better data, all data can't be perfect, so don't die trying. Certain decisions demand perfect data because of their importance, but the critical nature of decision timing fights against this desire. It is very easy to sit back and say that all data has to be perfect and not take any responsibility or action because the data isn't perfect. Don't get caught in that trap. On the other hand, don't stop investing in great data quality because it might cost some effort. There is a delicate and dynamic balance to be struck here. 

Art for the 3rd Quarter 2020

 I hope you and yours are doing well during this challenging year of 2020. My art business is getting an unexpected lift in sales demand and production. Here are some of the new pieces. One was a request from my granddaughter in Loveland Colorado. She wanted a painting of a Brontosaurus because she thinks that they are gentle dinos :) I also created two new paintings on a whim. The first was a raven flying past a full moon. It reminded me of my late father who had a raven for a pet. It sold immediately to a good Candian friend, Lin Whaley. The second was a night scene of a park in Paris that reminded me a night Sherry said "yes" in Paris in 1997. I posted it recently and sold a giclee to another friend Kari Moeller in Kansas City.  I also completed a brilliantly colored fractal for you to see. If you are interested in seeing my portfolio or buying a piece, please click here  Some of the newer pieces haven't made the website yet, so contact me at jim.sinur@gmail.com, if you have a desire. 

                                                          BRONTO 

                                                 RAVEN NIGHT

                                                   PARC DU PARIS

                                                   BIG BANG