InetSoft Product Information: Data Mashup Software

This is a table of contents of useful information about InetSoft's data mashup software which is included in its business intelligence application for dashboards, reporting, and analytics, Style Intelligence:

Example of Visual Analysis of a Multi-dimensional Data Set - I am suprised by how much interactivity there is this visualization dashboard. But I am wondering how do the slider bars work? Byron Igoe (BI): For instance in this little simple example of visual analysis of a multi-dimensional data set provided by the US Census Department, the slider is usually bound to your numeric data. Here you have got some sliders for these different pieces of census information. Question: Now are you able to implement a slider because you have got the data running in a cache or separate in-memory database? BI: So here is actually a pretty major technological differentiator from other BI solutions. Everything that we do is server-side. Whereas a lot of the other Flash-based dashboard products out there, it's basically a one-time compilation and one-time building of a SWF that then gets downloaded, a different SWF for each dashboard...

Examples of Data Mashups - I am going to just pick a couple of examples of data mashups and then go little bit deeper. The first one is an example of classic reporting, a daily sales report across multiple drugs for a biotechnology company. Part of that information comes from a Oracle database that has the North American sales and also the budget, but the problem is there are a lot of other inputs to the system coming from external wholesalers and distributors across 90 countries. So if you want to have a real time view then you needed to have a virtualization layer that has these data sources normalized and is basically accessing those information sources on demand to provide the real time views. Now it is easy to consolidate that data into a daily sales report that may be exposed as an executive dashboard. Now this doesn’t preclude that combination from also going back, in this case it’s shown as another database, but in effect going back to a data warehouse for our future or historical analytics. And in this process, data virtualization is accessing and converting semi-structured data providing a faster way to transform, match and integrate this as opposed to ETL’ing all of this, which would then introduce latency...

Click this screenshot to view a six-minute demo and get an overview of what InetSoft’s BI dashboard reporting software, Style Intelligence, can do and how easy it is to use.

Evolving a Rationalized Set of Canonical Data Models - The effect here is that, because we haven’t developed our environment 30 years earlier in anticipation of many different ways that the business was going to grow and change, we ended up with this complexity and variation. But once we have an understanding that those things can exist, we want to reduce the risk of doing the same things over and over again - replicated functionality, replicated work, rework by understanding where those differences are. We can start to migrate towards a more standard environment so we can assess the variances. We can look at what types of data standards we can use for bubbling up that chain of definition from the business term to the data element concepts to the uses of the data elements, the conceptual domains and the value domains...

First Step in a Data Virtualization Process - That’s the first step in a data virtualization process, to create this normalized or base model disparate data. The second step is to transform it, improve its quality and integrate it into new data models. The third step is to expose this information through as a virtual relational database or as a Web service, such as an XML feed, or something that can be accessed as a Java Object or as a Java Portlet or as a SharePoint Web Part. The reason you want to do that is so you have reusability of these data models to serve multiple applications. You are basically providing virtualized access. Now in runtime, any external application would call the dashboard or report created in this data mashup platform. The platform would understand the query, optimize it and may decide automatically or in design time whether to pull real-time or cached data, in which case a scheduler is invoked to pre-fetch the data. You are not doing a full-blown replication of a data store. You are only selectively using caches or a scheduler to complement virtualization...

For a Successful MDM Project - For a successful MDM project, it's important for the business side to be involved in the project in terms of setting goals and expectations. Some organizations are formally doing this collaboration through Centers of Excellence, Competency Centers and Advisory Councils, just to give a few of the names that these groups of champions and evangelists who regularly meet to review an MDM project are called. So we find that many organizations will start with this approach and try to get kind of an organizational or political kind of body together and then look for good reference data sources around the organization where data is managed well and begin to work MDM through a few related sources before trying to expand into an enterprise initiative. I should say that we have done some research in this area and 36%, according to one of our research studies, do have projects in place to be deployed across the enterprise, and another 44% said they started corporate projects in certain business functions or divisions but do envision rolling it out as an enterprise implementation...

Formula Tables - Formula tables are used to create real-time, spreadsheet-like reports with highly specific or complex layouts. These tables can be used to implement the kind of data grouping and aggregation which is commonly required in accounting and financial applications. Formula tables bridge the gap between spreadsheet applications (like Excel) and traditional reporting tools. In a spreadsheet, you usually 'fill' a column with data and then define summary formulas that reference different cells. A formula table is similar. Rather than bind the table to a query as a whole, you extract parts of a query result set and then dynamically fill the header rows and header columns of the table. You can then reference these 'filled-in' cells to perform statistical calculations in formulas...

Getting a Representative View of the Chain of Information - Here is a good example. I was once talking in front of an audience consisting of technology providers, actually software companies, and they said, very often what we will do is we will provide evaluation licenses of our software to prospective customers and we give them 30 days worth of customer service. Well, as far as the sales people are concerned, they are still prospects, they are not customers because they haven’t obliged by the rule of the definition of customer which is giving the company money in exchange for the use of a product. On the other hand, as far as the customer service department was concerned, those individuals were just as customers as anybody else who shared their money with company, because they were under the licensed evaluation agreement, they were provided full customer service or full customer support...

Goals in Operational Application Development - So if we just look at some of the goals in operational application development, they came up with the word agile. They just wouldn’t be more nimble in their work. And in a lot of ways agile is the wrong word. I think what we are all looking for is just to speed things up. And a lot of times, also with methodologies, lot of times people say, well you know the method is great, but I am a business man or woman. I don’t really care what the guys in the cubes do as long as they crank it out. Well, actually you should care especially in business intelligence because what the men and women are doing in the cubes takes a long time. And I mean we have all heard the classic complaint: ‘I just want a new report,’ or even simpler, ‘I just want a revision of an existing report, and it took six weeks for me to even get a response and another six weeks for kind of a review, a third six weeks for approval; six months out I am still waiting for this report.’ Where did it come from? And it’s no joke. The pace of business just accelerates so it’s really a need for the business people to get the products of business intelligence sooner to them because with the pace of business, especially where the recession drove all kinds of changes, even the recovery is driving changes because companies are trying to realign to the new reality, the new economy...

Good Data Discovery Tools - Are you searching for a good data discovery tool? InetSoft offers an easy to deploy, easy to use enterprise data visualization and dashboarding application...

Good Strategy Data Mining - This podcast is about how to develop a good strategy for data mining. Data mining is not likely to be fruitful unless the data you want to use meets certain criteria. Today we will talk about some of the aspects of the data and its application that you should consider. Is the data available? This may seem like an obvious question, but be aware that although data might be available it may not be in the form that can be used easily. You can input data from databases, via ODBC from files. The data, however, might be held in some other form or in a machine that cannot be directly accessed. It will need to be downloaded or dumped in a suitable form before it can be used. It might be scattered among different databases and sources and need to be pulled together. It may not even be online, If it exists only on paper, data entry will be required before you can begin data mining. Does the data cover the relevant attributes? The object of data mining is to identify relevant attributes so this may seem like an odd question. It is very useful however to look at what data is available and to try to identify the likely relevant factors that are not recorded. In trying to predict ice cream sales, for example, you may have a lot of information about retail outlets and sales history, but you may not have temperature and weather which is likely to play a significant role...

Hadoop and Business Discovery - We are hearing a lot about Hadoop and of course, before that we heard a lot about MapReduce, but Hadoop in particular is a very effective means for gleaning value from unstructured data. But there is a bit of a process that you have to work around. It’s not quite a straightforward as with traditional data warehousing. The Hadoop Technology (when it kind of entered the market a while back) created an awful lot of buzz and it has really great capabilities, but with that said working with the Hadoop open-source stack, it can be somewhat complicated it’s not quite as easy as advertised. And when you get vendors like InetSoft and others that have created ways to speak Hadoop stack and access that Big Data, they are really kind of solving some of the problems for you. And it’s certainly a trend that I have seen in the space that more and more of the innovative vendors are addressing the Hadoop stack in a way that’s kind of eliminating some of these scarier skill sets that might be required to get out that information and making it a lot simpler to utilize...

High Speed Parallel Processing to Connect to Data - Yeah, I mean, definitely the area we are seeing that like a local audience around the appliance area, the people putting in very high speed parallel processing to connect to data very, very quickly, but I think the performance that you want to output certain data fast, and you want to put other data on systems that needs to process slower than others in terms of their size. And again the ability to bring all that data together and place things that you have to repair the data, I think what is going to emerge out of the next year in terms of the business, the purpose is where they have designed but targeting the user where they came. Where did they come from? Richard Walker: Yeah. it's a good point, and I am going to another hardware piece. Last week I was at Teradata Partners Conference, and I saw an appliance there from Teradata that has solid state drives in it. So we are all kind of waiting around to see if solid state was going to kind of replace memory. What about flash memory? Is that coming on in the enterprise systems, that kind of thing...

How Data Mashups Work - OK, and Byron, let’s drill into the underpinnings of this stuff because we talked earlier about APIs and third party data, and so forth, and ideally with a mashup, again, you want to enable these end users to mix and match data sets very easily. So how do you deal with that marshalling area of data? Do you, for example, are you just exposing a range of data feeds, and is that in your product, or do you leverage another product? How does that work? So specifically in our product, it’s all homegrown technology. The common context, so to speak, is as Jim would say, at the metadata, always. So it doesn’t really matter where the data is coming from...

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