What in essence distinguishes the Dynizer from other competing platforms?
Three elements distinguish the Dynizer: It’s Simple - it has a generic data model based on Open World Semantics that turns all data into either a Who, a What, a Where or a When and allows us to see all the links between all of data; It’s Integrated - the Dynizer processes all kinds of data, whether that’s structured like a spreadsheet; unstructured like free text; or semi-structured which is a combination of the two. It’s Flexible - It’s one integrated platform which offers many different ways of exploiting data through queries, constraints and workflow.
You're doing something in big data?
No we're not. Big data is understood by most to be the successor to Business Intelligence. Actually, it acknowledges that most answers will be found in combining pieces of data coming out of a number of incomplete data sets. However the way in which classical big data solutions handle data incompleteness and distribution is outdated. We go beyond big data because we integrate and distribute data according to a completely new paradigm that uses open world semantics.
What is open world semantics?
Open world semantics is a new technique that makes use of the general characteristics of each data element to easily use it in a flexible way. For example: The person John Smith can be a supplier in one context; a customer in another; or a citizen in yet another. The link between the three different roles is the open world semantics characteristic that John Smith is a person - a Who. OWS is a simple abstraction method opening up unseen flexibility, integration and simplicity for data management.
Dynactionize is a new name in the data space, what’s your background?
Dynactionize is a growing young company built by entrepreneurs with a proven track record of innovation in data analysis. The company’s founders have worked with some of the biggest names in data-handling and media across the world.
Is the Dynizer the ultimate answer to all our business-based IT problems?
Of course, on one condition, that the problem can be solved by intelligently using all of your data.
Is the Analysis function within the Dynizer meant to replace a data warehouse?
Although the Dynizer was not specifically designed as a replacement of data warehousing, the overall architecture makes for a strong Analysis function, that under normal business conditions renders a data warehouse obsolete.
How efficient is the Dynizer?
We don’t become hung up on historical limitations on database architecture. Our ‘plan-analyze-archive-query’ approach means that querying, workflow and constraints are all integrated into the process, meaning that what you learn will be defined by the questions you ask, not by the information you already know. And the more data we process, the better the results we get.
Do you have to be selective in the data you analyze?
No. We believe in taking in the more data the better because we don't need experts to decide how we focus on, and build data models. We evaluate the performance of our analytics model performance in relation to the quality of results we achieve through the analysis itself.
Is your data analysis numerically based?
No, our analysis is an iterative process, not based simply on numeric data first - and we don't have to turn non-numeric data into numeric data to understand it. The platform handles both data-aware and data-unaware models. The data is quantified and typed.
Does the Dynizer consume a lot of computing power?
No, we offer the platform as service, so for you the IT overhead is minimal. What’s more, we know that the platform has to be available 24/7 as a baseline minimum.
How secure is the Dynizer?
We don’t impose a top-down security regime, we look to work with organizations to ensure the use of the platform is secure. That’s why we aim to make the appropriate data available to the appropriate users only at the appropriate time, based on agreed rules and criteria. All activities on the platform are timestamped and traceable.
Can the Dynizer answer questions like a human being?
That's a bit of a stretch, but what we do say is that often, the Dynizer, through making associations in data that the user might not even have considered, will create insights without necessarily being queried for them specifically. That's a bit like answering the question before it's been asked...
Is Dynactionize claiming that domain knowledge is no more relevant when implementing the Dynizer?
No. Domain knowledge remains relevant in order to get the right context at the right time. Using the Dynizer though, dramatically diminishes all kind of laborious tasks such as adding metadata to documents or developing thesauri, taxonomies, tag lists, topics, ontologies and the like, necessary for the adequate implementation of traditional solutions. Moreover, using the Dynizer will open the door to possibilities, which are only implementable on traditional software solutions with great difficulty or not at all.
How would the Dynizer behave handling large data sets?
The architecture of the Dynizer is distributed by design. We operate a complete separation between the actual data and the indexes. Queries are resolved by using the indexes only and the resulting IDs allow us to easily fetch the corresponding data from the storage. Both indexes and data storage are intelligently distributed to optimally use the capacity of the hardware to have no single point of failure in the system and to be able to execute queries in parallel without having to map and reduce.
Is the Dynizer a data analysis tool?
No, the Dynizer is a data management platform which, by recognising all data as either a Who, a What, a Where or a When makes it easier to analyze using lightweight applications.
Is the Dynizer a (proprietary) database?
Yes. But it's more than a database. It's a complete platform, delivered as a service.
Is the Dynizer a SQL database, or does it run one in the background?
No. But we handle SQL data and queries.
Can data be extracted from the platform in another, current, format?
Can standard query languages such as SQL be run against the stored data?
Will your platform replace the many different data application solutions I have?
It can do, because it is able to see all the links in data generated in vertical silos - seeing beyond the surface - and allows you to combine data elements coming from different silos to solve your data problems.
Does the implementation process of the Dynizer fit into commonly accepted approaches or is an entirely different set of knowledge and abilities required to be successful?
Dynactionize Implementation Services, a group of multi-role experts, would employ our Standard Implementation Methodology to get the job done as quickly and efficiently as possible. We would argue that organizations shouldn’t have to adapt the way they work to suit a particular software framework. The framework should adapt to them. By working closely with the organization, the team would adapt the Associative Data Model to best reflect the way the organization works. During implementation, the team would be on hand to ensure the particular solution was fully optimized before it was handed over to the people who best understand the way they work.
Do I have to sign a multi-year agreement to use the platform?
No, it’s available on a pay-per-use basis in a pricing policy to suit most requirements.
Do we need expert help to set up the platform?
There are many solutions where the experts will tell you the results you're going to get, not because they're particularly clever, but because they've engineered the solutions that way in the first place. Our analysis is not performed by external experts alone - it's for you to understand and use. To an extent automated algorithms in the Dynizer are maintained by experts, but we report all results and we don't rely on R and Hadoop or R and Spark for the analysis.
Is the platform designed to be used on a desktop PC?
As the Dynizer is a platform, any other device - desktop PC, tablet, mobile phone - is just a consumer.
Who is the platform aimed at? IT departments?
It's aimed at the people who create and use the data in their every day working life. Therefore, it speaks the language of action - doing something something with somebody, somewhere at some time. That's the language of business. It speaks for itself that if business users can work more efficiently and with less support from IT, also the CTOs and CIOs of an organization will be happy because it gives them time to concentrate on their real work.
Do I need a separate document management and/or archiving function when implementing the Dynizer?
The Dynizer can easily interact with and support current document management solutions. Because in dedicated packages document management and records management are often intertwined, modelling the specific relevant rules in an almost inseparable fashion, it is generally not useful to migrate them to the Dynizer as a goal in itself.
What can the Organize function in the Dynizer do for my business?
The Dynizer has two important components that work together by design: a workflow engine to model production processes and an advanced planning functionality that optimizes the logistics of these processes. Both functions are versatile and able to handle a myriad of processes, from complex document production with all kind of interdependencies, to optimized resource planning and logistics.
Is the Interactivity function of the Dynizer about the same as a CRM system ?
The Interactivity function helps build a complete view on customers and other relevant groups one might want to define, within the boundaries set by formal access rights, privacy regulations and in wider perspective, good conduct recommendations. So the Interactivity capability comes with more than enough functionality to keep the essence of doing business in focus as well as predefine and automate necessary interactions with customers. So, while it is not a CRM solution, with the qualification of customers, contract registration and the ongoing commercial (sales) process charted in a prescribed workflow, there really is nothing whatsoever, to prevent an organization creating an app on the Dynizer to do exactly that.
What’s the idea behind the Dynactionize Community?
We believe that the Dynizer is a powerful and innovative base from which organizations can start to address their growing relationship with data and what it can do for them. We don’t prescribe what organizations should and shouldn’t use the platform for, we just ask that if they come up with a particularly useful way of using the platform, that they share it - and in the rewards that may come from it.