How Can Data Visualization Help Me Achieve Business Results?

Reporting and Data Visualization Improves Team Understanding!

Statistics reveal that many people learn best when they see a story or information depicted in an image. Graphs, charts with colors, lines and shapes can often tell a story and communicate issues, challenges and opportunities in a business environment.

According to Forbes, ‘Almost eighty-thousand scientific studies attest that visual images promote retention.’

‘Visualization and presentation formats can include personalized dashboards and visualization techniques, alerts for exceptions and trends, and intuitive, mobile BI dashboards.’

Let’s consider a few examples of data presentation to illustrate how images, graphs, charts and visualization techniques can improve data understanding and retention.

How Can Data Visualization Help Me Achieve Business Results?

Cross Tabulation – Data presentation consists of categorization of data into groups, such as products, geographies, demographics, etc. It can be very useful in understanding sales results, product pricing response, target audience assessment, etc. Cross tab analytics can help your team understand market research, survey responses, seasonality and other factors.

KPI Reports – Key Performance Indicators (AKA KPI) can provide metrics in a dashboard environment that is easy to understand, so users can monitor and manage success factors, and quickly see where there are problems. KPI reporting can be used to identify and capitalize on opportunities and to adjust to challenges in the market and within the walls of the organization.

Custom Print Presentations and Reports – Every organization has a need for custom reports. Needs vary from division to department to user, and these needs can be expensive to accommodate. Custom reports to present data for decision-making, or to monitor results on an ongoing basis are crucial to the organization. But if the enterprise has to ask IT or business analysts or data scientists to satisfy the need, they are losing productivity, time and efficiency. By giving users the ability to design, format and product reports for a particular staff meeting or project, the enterprise can keep the process moving and ensure that the team has what they need to gather, analyze and understand results in a meaningful way. Custom formats might include customer statements, management reports, compliance reports, project templates, etc. Users can present data in a clean, colorful, attractive way to satisfy customers, partners, suppliers, executives and team members.

‘According to Forbes, ‘Almost eighty-thousand scientific studies attest that visual images promote retention.’

These are just a few examples of reporting formats and types, and how they might help your enterprise. Other types of visualization and presentation formats can include personalized dashboards and visualization techniques, alerts for exceptions and trends, and intuitive, mobile BI dashboards.

Team members, managers and executives typically think of reporting and presentation as boring, detailed and unintelligible. They rarely see the value in using data to make decisions when, in fact, this approach is the wisest and produces the best results. But it is understandable that the staff, customers, partners and suppliers would cringe when a report is placed in front of them, emailed to them or presented on a screen.

What if you could create, format, present and share data in a way that quickly communicated results, delivered a message, identified an issue or illustrate dan opportunity? Change the way your enterprise uses and interacts with data, with clean, clear, concise, elegant and colorful presentation.

Explore the benefits of Smarten Reports, and Pixel Perfect Print Reports and the use of this this seamless PDF Pixel Perfect Reports Solution, and the Smarten suite of Augmented Analytics can support your business users with self-serve tools that are intuitive and will encourage user adoption and fact-based decision-making.

Original Post : How Can Data Visualization Help Me Achieve Business Results?

Understanding BI Tools in Today’s Market

How Do We Define Business Intelligence Today?

Business Intelligence (BI) is the lifeblood of an organization. Without business intelligence, the enterprise does not have an objective understanding of what works, what does not work, and how, when and where to make changes to adapt to the market, its customers and its competition.

You may be interested to know that TechJury reports seven out of ten businesses rate data discovery as very important, and that the top three business intelligence trends are data visualization, data quality management and self-service business intelligence.

As the Business Intelligence solution market evolves, it may be difficult for an organization to know when to invest in these tools, and which tools are best for enterprise and user needs.

Context-Driven Natural Language Processing (NLP) Beats ‘Dumb’ NLP Every Time!

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 (NLP) Beats ‘Dumb’ NLP Every Time

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.