InetSoft Product Information: Analytics Dashboard Tools

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Taking the Pragmatic Approach to Big Data Analytics - This webinar is inspired by a series of reports a research group put out. The most recent was called “Analytics: The Real-World Use of Big Data.” Back in 2010, they published a study called Analytics: The New Path to Value. And in that study they took a high level look at the market and where organizations were placed along that maturity sophistication curve. In 2011, they followed that up with a study called Analytics: The Widening Divide, and in that study they took a look at those sophistication levels and where organizations were focusing and took it a level down into the organizations themselves and how they were organizing themselves and executing an analytics within their organization. This year came Analytics: The Real-World Use of Big Data. So that’s a subset of the overall analytics market focused on the Big Data topic. Some of the questions, not all of them, but some of them, carry through from year to year. But they really try to touch on what’s most timely for executives in the business market place around the globe to focus on...

Analytics Dashboard Tool Example
Click this screenshot to view a 3-minute demo and get an overview of what InetSoft’s analytics dashboard tool, Style Intelligence, can do and how easy it is to use.

Talking About Big Data - And in that context, what we have seen more and more of our customers coming to us, talking about big data for example, where we have large volumes of data, or we have different types of data or coming in at different speeds. So I think some of our more mature customers are also focusing on what are the best practices around sampling when it comes to big data. When it comes to data visualization, what are some of best methods to use? When it comes to transformations, there are question such as how do we handle missing values? That’s from the data preparation process, and a lot of our customers are looking into some of the best practices on that end. Moderator: When you talk about sampling, I am presuming you are talking about taking a small subset of your data and creating some algorithms using the subset. Obviously if you are trying to develop an algorithm based on a megabyte of data, it's going to run a lot of faster than if you try to do that on a terabyte of data. When you do sampling, what’s a good percentage of the total? Is there a best practice there...

Top Trends for Business Analysts - I would like to welcome you to today’s webinar, titled “Top Trends for Business Analysts.” The webinar will last for approximately 60 minutes including the Q&A session. So, make sure that you submit your questions in advance using the question’s feature in the webinar software. I have got to admit it’s always fun to sort of pontificate what’s going on based on some of the experience that occurred to us over the year and reflect on them. I a sure a lot of questions will be spurred, and I will address a lot of these questions as we go on in the presentation, so stay tuned. Slides will be available afterwards as well. So, without further adieu I’d like to share with you our 10 key business analysis trends for 2012. Also, as we go on we are going to be putting up poll questions, so there will be plenty of opportunity for you to voice your opinion and have a say in the webinar. So I am looking forward to hearing your responses to some of the questions we’ve loaded in, in the form of polls. Also I will do my best to answer questions as we go on fly. They are an awful lot of you and one of me, so if your answers scrolls through and I miss it inadvertently, I do apologize in advance, I promise I will do my best to try and get to everybody’s questions...

Read how InetSoft was rated as a top BI vendor in G2 Crowd's user survey-based index.

Top Data Analysis Tools - In order to gain insights, your organization needs a BI solution that not only reports current performance, but can also run analysis to predict future outcomes.The greatest return on your investment will be from a software that has both powerful and intuitive data analysis tools...

Three Dimensions of Analytics - Some people think about analytics as simply predictive type capabilities; others as advanced math, statistics; others as speed of thought visualization; and still others, maybe a little old school of thinking a bit, as multi-dimensional analysis, OLAP and things like that. So I don’t really have a great definition to give but I can tell you this: I have looked into analytics for quite some time now. And I will say that it has three dimensions...

Use Case of Maximizing Drug Launches with Analytics - The second use case that we're going to explore is really focused around drug launches and being able to maximize what that launch experience looks like. The key question that we're going to go ahead and shine a light on is how a pharmaceutical company might really be able to understand some of the early adoption related to their drug in the effort of being able to maximize their sales and being able to maximize their marketing launch as well. As many of you know, being able to understand the early adoption of a drug that you just launched to market is extremely important and critical to being able to understand the long term success of that particular launch. Now, there are a couple of different ways that you can actually think about how a drug is being adopted. But it's really important to understand the settings in which that drug is actually being used and prescribed. That might be understanding which hospitals have started to use your drug. That might be understanding which physicians have started to prescribe your drug. It's really kind of a starting point to understand the success of a launch...

Using Analytics to Increase Staffing Productivity and Improve Hospital Operations - Today we will highlight the many ways that our customers are using data to disrupt industries and business processes in the healthcare industry, specifically in the hospital management sector. Presenting for us today is the Director of Data Management at Centre Hospitalier Universitaire de Québec. At the hospital one of the research projects includes staffing workloads and productivity, operational metrics such as throughput, capacity management and regulatory compliance and more. Currently they are using AI and advanced analytics to predict outcomes related to sepsis, denial of paper resources, staffing and employee turnover. We have a team called Data Management and Performance Measurement. Let's call them DM and PM. Today we would like to share with you a little bit about of our hospital and our team. The hospital's mission is to take exceptional care of people. In doing that we have gone through a journey of transformation of knowledge, of position and growth, in which it depend on the right strategies and technologies. My team was created five years ago. The vision is to simplify technology for a dynamic success. In this five year journey, we will share with you how we did this in the five years. So today, 2019 is our fifth year in this journey. When we started out in our journey in the first year, because the needs are tremendous, we realized that we needed to maximize and develop availability of the information right away. In doing that, I would share with you in the next few slides...

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Visual Analytics Company - Are you looking for a good visual analytics company? Since 1996 InetSoft has been making business software that is easy to deploy and easy to use. Build self-service oriented dashboards and visual analyses quickly. View a 3-minute demo and download a free version...

Visual Analysis Examples - With its roots going back to 1996, InetSoft's visual analysis software Style Intelligence uses a reporting-driven approach to enable rapid deployment of analytical dashboards. Dashboard software has been established as a highly effective business intelligence tool. More than just monitoring-oriented or reporting-oriented, these tools support advanced visual analysis. Style Intelligence is not a desktop tool. While it can be run on the desktop for individual use, it is Web based server solution that enable visual analysis from any device with a browser. It is accessible on mobile devices. Take a look at the versatility of the visualization engine below. Click on the images to get a better look...

Visual Analytics Evaluation - Visual analysis is a relatively new innovation in information management software that allows a person to explore data in an interactive, visual manner. At its simplest, it means charting and graphing data, but the novelty is in multi-dimensional charting and interactivity. Multi-dimensional charting allows you to add coloring and implement sizing options. Coloring means coloring different data points on a two-dimensional chart to denote more information. For example start with a graph of sales opportunities where closing probability is depicted on the y-axis and days until expected close date on the y-axis, with dots represented a single opportunity. You would already be able to identify imminently winnable opportunities in the upper left corner. Now color the dots by sales person, a different color for each person. Now a scan of the color patterns shows who has more open opportunities and where they are in the likelihood and timeliness to close. Add another dimension by sizing those dots by dollar amount, such that the larger the revenue potential of the opportunity, the larger the circle is. Now, at a glance you can prioritize opportunities to focus on...

Visual Analytics Reviews - When it comes to business intelligence, a visually interactive data analysis capability is essential for proper forecasting and planning. As a well known name in the BI industry, InetSoft has been consistent in delivering one of the most agile and intuitive data analysis tools, provides aesthetically pleasing representations of data....

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Visual Analytics Software - Are you looking for a method to explore data in a simpler, more effective way than traditional static reports? Visual analytics software provides critical insight into solving problems and answering questions in data using interactive graphics...

What We Do with the Analytics Which Makes a Difference - Moving on, what we recognize is that analytics is not a destination. It's really what we do with the analytics which makes a difference. This slide indicates really that we can use analytics to ensure that the insurance company is meeting the strategy intended set out at the beginning, and if that strategy is being missed or diverted to make the right connection, analytics can help us in terms of the creation of new tactics to deliver on a strategic imperative, for example, or for the creation of best practices to modify our behaviors. The analytics solution can fit in many part of the organization through distribution, through to sales, supply chain, operational management, marketing, and claims. We will be talking specifically about a couple of those areas a little later. At the end of the day we're not doing this for the fun of it. It's around using analytics to change your behaviors and change our practices for an insurance company to obtain competitive advantage and to create a differentiated service and product, and ultimately to obtain profitable growth. We are nowadays in what's described as the fourth age of analytics, and it might be helpful for you as individuals just to think about where you sit in this particular hierarchy of analytics. The foundational analytics is very much the description level, the use of BI tools for reporting to identify what has happened and what is currently happening. The second layer of analytics is in the area of prediction which is our focus today which helps us anticipate what may happen and perhaps raise alerts or forecast. The third age is what we call prescriptive where we align rule based technology into our predictive models to help us automate our decision...

What-If Analysis - InetSoft's what-if analysis feature assists analysts in quantifying uncertainty in causal relationships and optimizing resource allocation while guiding decisions. InetSoft's Style Intelligence is the comprehensive real-time analytical reporting and dashboard software solution used at thousands of enterprises worldwide. View the example below to learn more about the Style Intelligence solution...

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What Makes a Predictive Analytics Enterprise - Essentially it is this cross-functional use of data directed from a strategic perspective to inform decision making across the organization that makes you a truly predictive analytics enterprise. What do we mean by that? Well, for example, marketing should interact with risk and understand the profiles of potentially high risk customers. You don't necessarily want to spend money enticing high risk customers to take your product. If you have analytics embedded across the organization at an enterprise level, you can ensure that you are attracting the right customer, and you're spending your money in the right way. Your company probably has a very wide range of individual customers with very different needs, and a significant proportion of insurance today is provided through brokers. Very often the first time a customer makes contact directly with the insurance provider is when they're in the position to make a claim. That makes it very difficult for an insurance provider to build a relationship with their customer. The goal for the insurance provider is essentially to ensure that the experience of the customer within the claim process is a satisfactory one and that it's tailored to the individual needs of that customer. I'd like to show you how predictive analytics can help you know your customer at that individual level...

Where Predictive Analytics Is Being Used - Where within the organization do we find predictive analytics being used? Predictive analytics historically has been in two areas. One of the most common uses has been within the marketing organization looking at the likelihood of individuals’ potential purchasing behavior of products and services. What are the influences and impressions of advertising? We’ve also seen predictive analytics used quite a bit for determining customer behavior. How do we optimize our interactions with our customers knowing that they’re going to react in certain ways based on their demographic profiles or their previous purchasing habits. We’re also seeing now how predictive analytics can be used across the manufacturing supply chain. We’re looking at things like mean time between failure and other particular processes that are well defined. Potential results will be known based on how things are operated. Besides marketing, customer facing issues and the supply chain, we also do see that many organizations are starting to apply predictive analytics into areas such as sales and finance and also looking at now the potential use of them in regards to working with suppliers and where materials are coming from to actually manufacturer products. Since there’s a lot of information that’s outside of our organization, we can start using predictive analytics as guideposts to everything from potentially prices of how companies stock is trading down to the commodity pricing of materials that are used for manufacturing products as well...

Click this screenshot to view a 3-minute demo and get an overview of what InetSoft’s analytics dashboard tool, Style Intelligence, can do and how easy it is to use.

Why Big Data Analytics Is So Important In Government - Today we’re going to talk about why big data analytics is so important in government globally, and especially in this economy. Commercial industry has been using data. The FedEx’s, the Wal-Mart’s, companies are really taking advantage of using their data, viewing it as an asset, making better decisions, faster decisions, and responding to shifts in the marketplace. Certainly in today’s environment the government is very interested in trying to do those same things. Budgets are shrinking. There are shortfalls in revenue. They just have to get smarter and better at what their doing. The Obama administration is out there promoting transparency, promoting visibility into what the government does, how they spend their money, the decisions they are making, and passing to on to every single citizen. So what they are doing today to put that in front, increase that visibility, make better decisions around policy, understand the direction of the country, itself, is very critical. In terms of where in the government the move towards better analytics is taking place, it’s in the financial departments of the various agencies. They are leading the way in terms of increasing that visibility of spending levels. Also, with healthcare reform, there is interest in knowing what is happening with costs and the aging population...

Why Do Companies Need Analytics? - Let’s start with a simple question of why? Why is it that companies need analytics? What is it that’s driving the urgency? The answer to that question is really closely tied to some of the main trends that we talked about before in terms of data users and time. So at the top of the list once we get once again we see data. Companies feel that all too often their most critical decisions are based on data that they have little faith in, either because it’s inaccurate, it’s dirty, it’s incomplete or sometimes just too fragmented or siloed within different departments. As we see with the third pressure on the chart here, the pressure also becomes evident from that business user perspective, that tactical or operational level. Companies struggle with getting the visibility they need into their key processes and then understanding what it all means. They look at analytics to help really sift through that operational data to produce insights that can help improve those processes. And lastly, we again see the urgency for analytics. A common reason why companies implement analytics, well it’s because people are clamoring for it. And not always technical people, line of business decision makers across many areas of the company again are raising their hands and asking for that better and deeper analytical capability...

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With Predictive Analytics It's Individualized Decision Making - In that particular case while the customer's claim is not being fast tracked, they are happy because they have an understanding of the length of time it will take to process their claims so they're not operating in the dark. Without predictive analytics, essentially it's simple rules based decision making, but it's more of a one size fits all manner of application. Whereas, with predictive analytics it's individualized decision making, and it's tailored to the behavior of the customer and other related data. The main benefit I guess in this particular instance of applied predictive analytics was the time to resolution. The claim is being resolved in a much shorter time, and the number of contacts required between the customer and the insurance provider has been reduced which leads to an increase in customer satisfaction and lower cost. I would also like to take a moment to remind you of the ability to use unstructured data to inform decision making. There was a lot of pretext information out there from interactions during phone calls that may be posted in social media. We have essentially seen and conducted analyses of the type of data, and we can see how it can be used to understand what is it these customers are actually saying. Also applying an appropriate framework to the study of these type of data ensures that you have an objective and repeatable and automated analytics process. Don't forget that the unstructured data is very valuable also...

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