This Client is a leading Financial Services and market data intelligence provider based in the United States. Its primary business focus is financial and commodity market intelligence and analytics. The Client offers cloud-based and real-time data access through a webservice interface to their clients, to enable clients to search financial and market data across multiple stocks, commodities, and exchanges around the world.
Year: 2022
The Angular Application Development environment is quite popular among developers and supports hybrid and cross-platform mobile application development with tools and an environment that makes development fast and easy.
Embedded BI Extends and Expands the Useful Life of Enterprise Solutions!
Businesses develop and/or license software solutions for a variety of reasons. Most enterprises invest in software to solve a problem, perform tasks, etc. But the useful life of a software solution and the breadth and depth of its overall value can often fall short of expectations for return on investment (ROI) and total cost of ownership (TCO).
‘By adding the value of Embedded BI with integration APIs, the team can achieve results, better leverage and use data by producing actionable reports and clear insight, and extend the useful life of the existing software applications.’
In order to leverage the full value of your users’ favorite software application and to increase user adoption, an enterprise can add embedded BI and augmented analytics. By providing seamless access to analytics in a single sign-on environment, the organization can ensure that business users get the tools they need to make recommendations, support decisions, report on progress, solve problems and identify opportunities, thereby improving the value of the existing software solution and the value of the team member as an asset to the organization.
With the right augmented analytics solution, business users can enjoy the advantages of sophisticated BI tools without additional training or complex processes and queries. Analytics are embedded via APIs for a seamless, scalable approach to analytics without a lengthy integration or implementation process.
According to Forbes, ‘the average single application today is powered by 18 APIs. Half of all B2B collaboration happens through APIs. And most staggeringly — 83% of all web traffic is attributable to APIs.’
Embedded BI with integration APIs offers numerous benefits including:
- The best of analytics and best practices of application integration to produce results and encourage user adoption
- Expansion and improvement of the value of existing software applications by adding integrated analytics
- The use of data within an existing application or software product to produce meaningful analytics and reports
Every business management team looks hard and long at software investments. These investments are typically expensive and time-consuming and often over promise when it comes to results. But once committed, these investments must be justified and cannot be undone without a lot of difficulty, confusion and complex backtracking. After the implementation, the IT team and business users are committed to the use of the software (whether it is helpful or not) and business managers find themselves in a quandary. They need the software to perform certain tasks but the software does not provide the promised value, ROI or TCO.
By adding the value of Embedded BI with integration APIs, the team can achieve results, better leverage and use data by producing actionable reports and clear insight, and extend the useful life of the existing software applications – all without requiring extensive training or complex implementation and additional high-cost investments.
‘In order to leverage the full value of your users’ favorite software application and to increase user adoption, an enterprise can add embedded BI and augmented analytics.’
Leverage the Smarten approach to Embedded BI And Integration APIs to add powerful functionality and provide access to existing ERP, SCM, HRMS, CRM or any other products and to provide analytics capabilities within existing products without major Investment. Reduce time to market and stay ahead of the competition!
Original Post : Embedded BI with Integration APIs Leverages Tech Investments!
If you are an avid reader of technical research or industry journals, you probably know about Natural Language Processing or NLP. If you don’t know about it, you certainly use it every day – whether you know it or not! When you search using Google, you are using natural language and that makes it easier for you to develop a question and get an answer. Ask a question and get an answer. It’s that simple!
But, when it comes to analytics, NLP is typically much more restrictive. Talk all you want about machine learning and natural language processing but the boundaries and restrictions placed on these concepts in a typical analytical solution do not make it as easy as business users might like.
Remember that your business team members are also consumers outside the walls of the office and they use and appreciate the ease of Google searches. Here, a consumer might ask, ‘how many ounces in a pound’, or ‘what is the tallest building in the world’, and they get an immediate answer. THAT is what they want in analytics as well and if you don’t give it to them, they are unlikely to adopt the analytical tools you invested in or to achieve the results you wanted for optimizing resources, improving productivity and, most importantly, engaging in fact-based decision making that will improve the business bottom line.
So, what, if anything can one do about the disconnect between the ease of use of analytics and the typical NLP solution? To answer this question, we first need to understand the difference between standard natural language processing in analytics (AKA Dumb NLP) and context-driven searching using natural language processing (AKA Intuitive NLP).
Context-driven natural language processing allows people to think and communicate like people – not like machines! It is intuitive and ‘smart’ and goes far beyond ‘dumb’ NLP.
Dumb NLP: The use of NLP in analytics provides the basic foundation to get a user into the details of the data and allow them to choose and filter using columns and filters. It recognizes the data in the column or field but not the context. Much like a text to speech solution, it can read, translate and present the data but it has no real understanding of what the data means. Users often get frustrated when they try to use these tools because they have to wade through the choice of columns, click on menus and sift through scripts and when the NLP query results are presented, they may discover that they did not get what they wanted because they omitted or included some inappropriate data.
Intuitive NLP: Context-driven natural language processing allows the user to think of a question and ask that question in a way that supports human thought, and natural communication. Context-driven NLP ‘understands’ and interprets the question and the user intention so, for example, if a user wants to find sales results for a product sold during the ‘Thanksgiving’ season, they do not have to know the date for a particular year or years. They can simply ask the question. ‘How many donuts were sold in Scottsdale, Arizona during Thanksgiving 2019 and 2018? The system will understand the question and interpret it to provide the right information.
Much like your best friend can understand your intent and respond to a question without your being concise or detailed, context-driven NLP can handle the subtleties and the context without the need for excruciating detail and restrictive programming or scripting.
Ask, ‘What was the best day of bakery sales in Tucson Az last year?’, and the system will know that, a) the ‘best day’ means best day of sales for you, that b) bakery sales means all items that fall within the bakery category in your product portfolio, such as cake, brownies, croissants, cookies, bread etc., c) that Az means Arizona and that d) last year was 2019. Just ask the question…and you will get an answer. It’s that simple.
Context-driven, intuitive NLP provides many opportunities to ask questions and handles many concepts, including,
Synonyms, Phonetics and Abbreviations – Enter question and the system will recognize and process information correcting for spelling errors, abbreviations and related words.
Geography, Places and Persons – Enter a question and allow the system to identify a person or place automatically, and give the answer in context of person or geo location.
Time Series – Enter a question and receive results based on absolute time, or on a range or relative time period.
Rank and Polarity – Enter a question and receive results based on a determination of ‘higher’ or ‘lower’ results.
Aggregation – Enter a question to understand results for averages, minimum, maximum, first, last, sum, counts, etc.
Comparison – Explore how sales or other factors compare from one region, year or variable to another.
Context-driven natural language processing allows people to think and communicate like people – not like machines! It is intuitive and ‘smart’ and goes far beyond ‘dumb’ NLP by offering tools that users will want to leverage and interacting with users in a way that is meaningful to them. Your business users don’t need have to use or understand sophisticated skills to create a query or ask a question. They don’t have to wade through five or ten steps to create a query. With context-driven NLP, users just have to think of a question and type that question and they will get the answers they need.
Make your business more productive, optimize resources, empower your team members and allow them to make confident, fact-based decisions and to solve problems and get the information they need to do their job – without stress or time-consuming training or procedures! THAT is the difference between using ‘dumb’ NLP and using intuitive (context-driven) NLP in analytics.
The Importance of Adding a Mobile BI App to an Augmented Analytics Strategy!
Many businesses are considering, or have implemented, business intelligence and augmented analytics solutions. According to renowned technology research firm, Gartner, ‘80% of organizations seeking to scale digital business will fail because they do not take a modern approach to data and analytics governance.’ With this prediction in mind, the addition of business intelligence and augmented analytics to the organization workflow, business processes and technology infrastructure is a wise decision.
‘The addition of mobile capability will improve user adoption, support culture changes and extend the office environment for a more productive business and team foundation.’
In order to address the ‘modern approach’ Gartner describes, the business must include a mobile BI and augmented analytics app strategy. In this article, we discuss the importance of including a Mobile BI App in the organizational approach to business intelligence and advanced analytics.
Changing the Culture and Business Processes
With any data literacy and data democratization effort, the business MUST look at culture change. If it intends to encourage business users to transform to Citizen Data Scientist, it must look at all aspects of its culture, business processes and workflow, and to integrate data sources and make that information available at appropriate levels so that users can access and analyze data and IT and senior management can be assured of appropriate data governance. When the business implements a business intelligence and/or augmented analytics solution, it must consider the importance of adding the capabilities of a Mobile BI App so that users can access data from anywhere. By providing mobile augmented analytics, the business can enforce and enable the culture change and modernize its approach to data access and data sharing. Providing restrictive business intelligence or analytics solutions without mobile capability will further inhibit user adoption and act as a barrier to the culture change within teams.
Extending the Office Environment
Over the past decade, businesses have changed drastically and one of the greatest changes is the concept of a ‘team’ or ‘group’ working on a project, or toward a goal. In recent years, the idea of remote workers has grown exponentially, and teams spread across the country (or across countries) and geographic locations are now using software and technology to collaborate and share data. Users want to access data on the road, in a hotel room, while working at a client office or in an airport, and when it comes to analytics, that need is just as great. It is important to provide a solution that accommodates all types of devices from desktops and tablets to iOS and Android devices, so that the user can access data and analytics from anywhere on any device.
Improving User Adoption
When senior management teams announce a new initiative like the adoption of analytics, it is easy for team members to discount the commitment and to believe the new ‘flavor of the month’ will simply disappear and they will go back to the old way of doing things. The culture change we discussed in this article is a necessary component and the availability of the tools, and easy-to-use solutions that require little training is crucial. A mobile BI and augmented analytics app meets the expectations of users for intuitive tools – tools that are accessible as and when they need them, and with simple, powerful reporting and collaborative tools, the users will be encouraged and enabled and user adoption will improve.
There are many other important aspects of mobile BI and augmented analytics. Here, we have provided a few of the crucial considerations a business must include when it reviews its requirements and builds a strategy to implement business intelligence and analytics for business users. The addition of mobile capability will improve user adoption, support culture changes and extend the office environment for a more productive business and team foundation.
‘In order to take a ‘modern approach to BI and analytics, the business must include a mobile BI and augmented analytics app strategy.’
Explore Smarten Mobile Augmented Analytics And Mobile BI and add powerful functionality and access for your business users with out-of-the-box Mobile BI and advanced analytics for every team member in your enterprise. For more information on Mobile BI and Augmented Analytics, read our articles, ‘Considering a Mobile BI App? Understand the WHAT of Mobile Augmented Analytics Before You Choose’, and ‘What Should My Business Consider When Selecting a Mobile BI Solution?’
Original Post : Improve Analytics User Adoption with Mobile BI App!
Is Your Business Considering Digital Transformation? There Are Many Benefits!
Consulting firm Deloitte states that, ‘Companies that have higher digital maturity reported 45% revenue growth compared to 15% for lower maturity companies.’ If your business is considering a Digital Transformation (Dx) initiative, it is with good reason – the transition can improve revenue growth, productivity, competitive positioning and enterprise agility.
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Original Post : Smarten Support Portal Updates – July – 2022!
This Client is based in the United States and provides a technology platform for Sleep Center operators to enable automation of back-office operations. The Client offers an end-to-end cloud-based and real-time platform to support consultation, clinical notes, billing, payments, comprehensive workflow automation and data storage with built-in Electronic Health Records (EHR) and Durable Medical Equipment (DME) modules, custom reporting and comprehensive visibility into daily operations.
With the Right Augmented Analytics You Can Satisfy Business Users and Data Scientists!
The renowned technology research organization, Gartner, states that ‘30% of organizations will harness the collective intelligence of their analytics communities, outperforming competitors that rely solely on centralized analytics or self-service.’ To achieve these goals, businesses must provide analytics and tools that are suitable for business users, and for data scientists and business analysts and all others who will participate in data analytics to achieve goals and objectives – in other words, a solution that will meet the needs of every user in every role in the enterprise!
‘Solutions that are designed to support users and roles working at all levels can ensure user adoption and optimize the contribution of data champions, business users, data scientists and IT.’
When a business considers the analytics solution market, it may find a variety of options, from restrictive, complex solutions to simple solutions designed for business users. It is difficult to create a balance and find tools that will be sophisticated enough to provide the support a data scientist needs and wants while still offering business users with average technical and analytical skills a solution that allows them to participate in new data literacy and data democratization initiatives.
A business can use spreadsheets and complex algorithms to perform analytics, or it can select a robust solution, deeply engrained in analytical techniques and designed for those with advanced training. But those options do not allow business users to participate!
Achieve Balance Between Function and Usability
When a business chooses an augmented analytics solution, it can satisfy the needs of business users with sophisticated functionality that is ‘built-in’ and will allow swift, accurate analytical activities without advanced skills. That same solution should also offer more advanced options and tools to enable data scientists, business analysts and IT team members to work at a level that is commiserate with their needs and roles and will integrate with tools they need and use on a daily basis, e.g., R Script, etc.
Choose a Solution that is Mobile and Accommodates User Needs
Complex, restrictive solutions do not easily lend themselves to a mobile environment. A myriad of columns and required field choices, will not allow users to access and report easily on mobile devices. Choose a solution that allows users to leverage desktops, tablets, iOS or Android devices and provide simple navigation and tools that can be used by any and all users on the road, in the office or working remotely.
Select a Solution that will Grow with the Enterprise
The need to add functionality or customize features can become costly and can mean that upgrades and user needs will be left behind in favor of budget restrictions. Choose a solution that makes it easy to add users, to personalize and customize dashboards to satisfy advanced users and to provide flexible reporting and infrastructure and licensing to ensure that the solution will grow with the organization.
Encourage Collaboration and Embrace New Roles
Traditional analytics solutions are designed to support advanced skills and roles. Solutions that are designed to support users and roles working at all levels can ensure that data champions, business users, data scientists and IT can collaborate, share creative analytics approaches and build data literacy and data democratization across the enterprise.
‘Businesses must provide analytics and tools that are suitable for business users, and for data scientists and business analysts and all others who will participate in data analytics to achieve goals and objectives.’
Advanced analytics solutions can be expensive, time-consuming to deploy and upgrade and difficult to optimize. These solutions are not meant to accommodate the skills and needs of business users. But the organization does not have to sacrifice functionality and advanced capabilities in order to give business users what they need. By selecting an augmented analytics solution that is comprehensive and advanced, the business can have the best of both worlds and satisfy the needs and roles of data scientists and business users.
Explore the advantages of Augmented Analytics Products And Services. Let us help you implement a solution that will be suitable for your team members and your business results.
Original Post : Augmented Analytics for Business Users and Data Scientists!
Why Should My Business Consider .NET for Software App Development?
Futurum reports that IT, customer care functions and marketing departments are currently focused on technology adoption, and that HR, manufacturing and legal functions are most likely to adapt to technological change in the coming years.
