Why choose- Nevron Chart for SSRS, Microsoft SQL Server Reporting Services (SSRS)

Why Choose Nevron Chart for SQL Server Reporting Services?

While SSRS 2005/2008/2008R2/2012/2014 come equipped with a free chart report item and with chart report items available from other vendors, you may ask yourself: Why use Nevron Chart for SSRS in my reports? This article gives a brief overview of the benefits of using our charting solution in your reporting projects.

Charting Types

Best Practices for Using Bar Charts Keep it simple: Use a simple and clean design for your bar chart. Avoid adding too many colors or other design elements that can distract from the data. Choose the correct type of bar chart: There are many different bar charts, such as stacked, grouped, horizontal, etc. Choose the type that best suits the data you are trying to visualize. Label your axes: Always label the x and y axes to clarify what the data represents. Include units of measurement, if applicable. Provide context to the data by including a title or subtitle explaining what the chart represents and any meaningful information relevant to interpreting the data. Order your bars: Order your bars logically, making it easy to compare data. For example, you may want to order bars alphabetically or chronologically by size. Use appropriate scales: Choose an appropriate scale for your y-axis. This will depend on the range of values you are visualizing. Highlight important data: Use color or other visual elements to highlight important data or trends. For example, you may want to use a different color for the highest bar in a group. Avoid clutter: Avoid cluttering your bar chart with too much data. Suppose you have a large amount of data to present. In that case, it may be beneficial to consider using a combination of multiple charts or alternative visualization types to display the information more effectively.	Best Practices for Using Pie Charts Make sure the data is suitable for a pie chart When considering whether to use a pie chart, it's important to ensure that the data is suitable for this type of visualization. Pie charts are designed to show how a whole amount is divided into distinct parts and are most effective when the data is categorical, and each category represents a portion of the whole. It's also important to remember that the primary objective of a pie chart is to compare each group's contribution to the whole, as opposed to comparing groups to each other. If your data doesn't fit these criteria, choosing a different type of chart or visualization may be more appropriate. Include annotations Annotations are a crucial element in pie chart visualization as they provide precise information about the proportion of each category level. Pie charts can be challenging to interpret accurately, especially for not easily recognizable values such as small fractions. Additionally, pie charts often lack tick marks to estimate values directly from slice sizes when depicting amounts rather than proportions. Annotations help overcome these challenges by clearly understanding the data presented in a pie chart. Consider the order of slices Arranging the slices in a logical order can enhance the comprehensibility of a pie chart. Typically, the slices are ordered from largest to smallest, especially when categories have similar values. However, if the categories have a natural order, it is recommended to arrange the slices accordingly. In addition, it is advisable to start the slices from a cardinal direction, either from the right or the top, which are the conventional directions for measuring angles. Although starting from the top may seem more intuitive, given how we read from top to bottom and view time progression, starting from the right is mathematically grounded. Avoid distorting effects To ensure an accurate interpretation of a pie chart, it is crucial to maintain the correct area, arc length, and angle for each slice. It is essential to avoid any distortions that could misrepresent the data. Specifically, it is recommended to prevent 3D effects that could stretch or squish the circle and create unnecessary depth, as this can skew the size comparison of each slice. Another potential distortion to avoid is using "exploded" pie charts, where slices are pulled out from the center to emphasize specific data points. This can make it difficult to accurately determine the part-to-whole comparison due to gaps in the chart.	Best Practices for Using Line Charts Selecting the proper measurement interval Selecting the appropriate measurement interval is crucial when creating a line chart. The measurement interval, or bin size, should be sufficiently broad and short, as this can result in hiding the helpful signal or revealing only noise. It's best to test out different intervals or rely on domain knowledge to make an informed decision. Using multiple lines, one for a fine-grained interval and another for the overall trend can also be useful. This can involve averaging over a rolling window to obtain a clearer picture of the data trend. Do not overload it with too many lines To prevent clutter and make the line chart easily interpretable, limiting the number of lines plotted is crucial. It's recommended to keep the number of lines to five or fewer. Too many lines on a chart make reading and understanding the data trends difficult. But if the lines are distinct and separated, it's possible to include more lines while maintaining the chart's readability. Use colors and markers effectively Using colors and markers effectively is key to creating a visually appealing and informative line chart. Colors can differentiate between multiple lines or data sets, making it easier for viewers to identify and track specific trends. Markers can be utilized to draw attention to particular data points or trends, emphasizing their significance in the overall pattern. It is essential to select appropriate colors and markers that complement each other and are easily distinguishable, ensuring that the chart remains straightforward and easy to interpret.	Best Practices for Using Area Charts Include a zero-baseline It is a good practice to have a zero baseline when using shading in a line chart or an area chart, as this allows for an accurate comparison of the sizes of each group's values. Without a zero baseline, the group values ratio may not match what is shown in the plot. While it is generally recommended to have a zero baseline in a shaded area chart to compare the sizes of different groups accurately, there are some exceptions. For instance, when comparing two series in an overlapping area chart, limiting the shading to the area between the lines instead of extending to a common baseline allows for zooming the vertical axis limits into the area of interest without requiring a baseline. In such cases, the shading represents which group has a higher value, and the color's intensity indicates the difference's magnitude. Limit the number of series in overlapping area chart As the number of series increases in an overlapping area chart, the number of color combinations also increases. This can make it challenging to interpret the chart, as most colors will only be associated with one group. When comparing two series in an overlapping area chart, it is easy to mistake it for a stacked area plot if one series is consistently larger. The overlapping colors can also confuse readers, as they are not included in the general legend. It is best to limit overlapping area charts to only two series and consider using a line chart to show the comparison between groups more clearly. Consider the order of areas in the stacked area chart The sequence in which the areas of different groups are arranged for plotting does not change the shape of a plot, but it can affect visualization reading. Placing the largest or most stable groups at the bottom and the smallest or most variable groups at the top can improve readability. This makes the most important group easily distinguishable as the bottom-most.	Best Practices for Using Line Charts Choose an appropriate scale: Ensure that your chart scale can accommodate the range of your data without distorting it. You can use a linear or logarithmic scale, depending on the nature of your data. Use consistent colors: Use consistent colors to represent the same data category across different float bars. This will make it easier for viewers to compare and contrast the different bars. Provide clear labels: Make sure each float bar has a clear and concise label that accurately describes the data it represents. Use descriptive labels that are easy to understand. Sort data categories: If possible, sort your data categories logically. This could be based on size, value, or other relevant factors. Sorting the data categories will make it easier for viewers to identify patterns and trends. Keep it simple: Avoid cluttering your chart with too much information. Only include relevant data to the message you are trying to convey.	Best Practices for Using Point Charts Creating an effective point chart (or scatter point chart in case more than one variable is specified) involves adhering to several best practices to ensure clarity, accuracy, and usability. Here are some key guidelines: Keep it simple : Avoid adding too many data points to the chart, as this will compromise its readability. For example, while the chart can handle easily hundreds of thousand of data points, plotting such a dataset will most likely result in a point cloud. Consider using sampling or clustering techniques to reduce the number of visible data points. Use consistent colors: If a fourth dimension of data is not required, you can use colors that have sufficient contrast from the chart background - for example darker colors on a white background or vice versa. You should also avoid close colors if you plot different data sets as this can also compromise legibility. Choose correct axis scale: For datasets with values that differ drastically in magnitude, consider using a logarithmic scale to present the data more concisely.
Best Practices for Using Bubble Charts Bubble charts are a powerful data visualization tool that can help you understand complex datasets quickly and easily. They're beneficial for displaying data with three dimensions: size, value, and category. However, like any data visualization tool, there are best practices that you should follow to ensure that your bubble chart is effective and easy to understand. Choosing the right data Firstly, choosing the right data to display in your bubble chart is essential. Bubble charts work best with data that has clear categories and a range of values. This will help ensure that your chart is easy to read and provides valuable insights into your data. Choosing the right scale Next, choosing the right scale for your bubble chart is important. You should choose a scale that fits your data and is easy to read. It's also important to ensure that your bubble sizes are proportional to the data they represent. Use color effectively Another best practice for using a bubble chart is to use color effectively. Color can represent different categories in your data in which case you should aim to use visually distinct colors. Alternatively, color can be used to represent a dimension in the data set, and in this case, you can use a palette to denote a range of values for the different colors. Labeling Finally, it's crucial to label your bubble chart effectively. This means including clear and concise labels for each category or value and providing a legend to help users understand what each bubble represents. By following these practices, you can create a compelling and easy-to-understand bubble chart that provides valuable insights into your data. Remember to choose the right data, scale, and color, and label your chart effectively to ensure it's as valuable as possible for your audience.	Best Practices for Using Surface Charts Surface charts are a great way to visualize data in three dimensions, making it easier to identify patterns and relationships. Here are some Best Practices for Using Surface charts effectively: Choose the right chart type: Surface charts are ideal for visualizing data with variable elevations and regularly spaced X/Z coordinates. If the data does not meet these criteria you can consider using the Mesh or Triangulated surface charts. Use appropriate lighting: Lighting can significantly impact the appearance of Surface charts. Use lighting that highlights the important aspects of the data, such as areas of high or low value that don't obscure any important details. Simplify the data: Mesh Surface charts can contain millions of data points, and rendering such an amount of data points, especially interactively is very computationally expensive. You can use various methods to simplify the rendered data set like binning or clustering, which are built into the chart. Use appropriate labeling: Labeling ensures the viewer understands the presented data. Label the axes and provide a legend explaining the meaning of any color schemes used in the chart.	Best Practices for Using Mesh Surface Charts Choose the right type of chart: Mesh Surface charts are best used when displaying irregularly spaced 3D data that is orderded in a grid. In some cases it may be more appropriate to use a Grid Surface (when all data points have common X/Z coordinates), or Triangulated Surface (when the data points are not ordered in a grid). Simplify the data: Mesh Surface charts can contain millions of data points, and rendering such an amount of data points, especially interactively is very computationally expensive. You can use various methods to simplify the rendered data set like binning or clustering, which are built into the chart. Label axes clearly: Label the x, y, and z axes to ensure the chart is easily interpretable. Include units of measurement if necessary. Use lighting and shading appropriately: Lighting and shading can enhance the 3D effect of Mesh Surface charts. Experiment with different lighting and shading options to find the best way to represent your data. Provide context for the data by including a title, captions, and annotations. Explain the purpose of the chart, the meaning of the data, and any relevant background information.	Best Practices for Using Triangulated Surface Charts Choose the Chart Type: The Triangulated Surface Chart best displays data sets that contain XYZ coordinated without any order. In case the data set implies an order for the coordinates, or the coordinates have common X/Z values, you can consider using the Mesh or Grid surface charts, as constructing a Delaunay triangulation is computationally expensive. Choose the Right Color Map: Choose a color map that best represents your data. A good color map should provide contrast and allow users to identify areas of interest easily. Label Your Chart: Add labels and annotations to your chart to provide context and make it easier for users to understand the data they view. Customize Your Chart: Use the chart's customization features to customize the appearance of your chart, including shading, labels, and annotations. This can help make your data stand out and make it easier to read. Use Appropriate Scaling: Ensure your chart is scaled appropriately to represent your data accurately. Use the chart's axis scaling features to adjust the scaling as necessary.	Best Practices for Using Vertex Surface Charts Choose the Proper Surface Chart Type: The Vertex Surface (Free Surface) Chart is used when other charting types cannot display the specified coordinates in a specific order or the surface cannot model a particular object. Choose the Right Color Map: Choose a color map that best represents your data. A good color map should provide contrast and allow users to identify areas of interest easily. Label Your Chart: Add labels and annotations to your chart to provide context and make it easier for users to understand the data they view. Customize Your Chart: Use the chart's customization features to customize the appearance of your chart, including shading, labels, and annotations. This can help make your data stand out and make it easier to read.	Best Practices for Using Radar Charts Keep it simple: Avoid cluttering the chart with too many variables, making it difficult to read and interpret. Use color carefully: Choose colors that are easy to distinguish from one another, and avoid using too many colors, as this can also make the chart difficult to read. Label clearly: Ensure that each axis is labeled clearly and that the labels are positioned in such a way that they are easily visible. Scale consistently: Use a consistent scale across all axes to ensure that the chart accurately represents the data. Consider using multiple charts: If you have a lot of variables, consider breaking the data down into smaller groups and creating multiple radar charts to make it easier to read and interpret. Provide context for the data by including a title, legend, and any relevant notes or explanations. Use appropriate data: Make sure your data is relevant for a radar chart. Radar charts best compare relative differences between variables rather than showing precise values. Test for readability: Before finalizing your chart, ensure it is easy to read, understand, and make any necessary adjustments.
Best Practices for Using a Polar Chart Polar charts are a powerful tool for visualizing data that depends on angle and magnitude. To ensure that your polar charts effectively convey your data and insights, consider the following best practices: Choose an appropriate data set: Polar charts are most effective for data sets that depend on angle and magnitude. Consider whether this chart type is the best choice for your data. Label your axes: Label your angle and value axes to ensure users can easily interpret the data. Use clear and concise labeling that is easy to understand. Use appropriate scaling: Choose a proper scaling for your chart to ensure all data points are visible and easily interpreted. Consider using logarithmic scaling for the polar value axis for data sets that contain data that differ in magnitude. Optimize axis positioning: Ensure that your angle and value axes are positioned to maximize clarity and readability. Use evenly spaced intervals and appropriate ranges to optimize axis positioning by using the axis docking and reflection paint features. Use color coding: To enhance readability or to add another dimension in data, consider using color coding or palette filling of the data.	Best Practices for Using High-Low Charts Choose the appropriate data: High-Low charts are most effective when used with data that consists of two variables (high and low), such as stock prices or weather conditions. Ensure that the data you are using is suitable for this chart type or it is best to use another one like Area. Use clear labeling: Make sure to label each axis clearly and concisely to help users understand the displayed data. This includes marking the x-axis (usually time) and the y-axis (usually values). Use color coding or shading: Consider using color coding differentiate between different data sets or to highlight specific trends or changes over time.	Best Practices for Using Error Bar Charts Choose the appropriate type of error bar: Error bars can optionally display the statistical error in the X, Y, or Z dimension, making any combination possible such as XY, XZ, or YZ. Ensure that the data has error information if you want to use this type of chart. Ensure the error bars are clearly visible: It's essential to ensure that the error bars in your chart are clearly visible. Additionally, the color and thickness of the error bars should match the overall chart design to maintain consistency and clarity. Use appropriate scaling: The scale of the chart should be suitable for the range of the data. The error bars may be difficult to interpret if the scale is too large or too small. Provide context: Error bars should be interpreted in the context of the data set and the research question. Providing labels, titles, and captions can help provide context and clarity.	Best Practices for Using Funnel Charts Use meaningful stage names: The stage names should be descriptive and meaningful so it's clear what each stage of the funnel represents. Order the stages logically: The categories should be ordered in a logical sequence that reflects the data flow through the funnel. Use consistent units: Make sure the units used for each funnel stage are consistent throughout the chart. Avoid too many categories: A funnel chart with too many categories can be overwhelming and difficult to read. It's best to limit the number of categories to 5-7, if possible. Highlight the drop-off rate: Use color or other visual cues to highlight the drop-off rate at each stage of the funnel, as this can help identify areas for improvement.	Best Practices for Using Box and Whiskers Charts Use Box and Whiskers charts to compare data: Box and Whiskers charts are excellent for comparing data between different groups. Use them to compare data points across multiple categories or periods. Label your chart clearly: It's important to label it with a clear and descriptive title and label the axes with meaningful units of measure. Ensure your data is accurate: Check it carefully before creating your chart to ensure it is accurate and up-to-date. Include relevant statistical information: Include relevant statistical data in your chart, such as the median, quartiles, and outliers. Avoid clutter: Avoid cluttering your chart with too much information. Use a clear and simple design to make it easy to interpret the data.	Best Practices for Using Combo Charts Combo charts are helpful when you want to display multiple data types on a single chart. Here are some best practices for using combo charts: Choose the right chart types: Combo charts can include any combination of charts, such as bar, line, scatter, etc. Choose the chart types that best represent the data you want to display. For example, if you show how sales revenue and profit margin change over time, a line chart might be best for revenue, while a bar chart might be best for profit margin. Use consistent axes: When using multiple chart types on a single chart, it's important to ensure they are consistent across all the chart types. This means that the scales and units used on the axes should be the same. If the scales or units differ, it can be difficult for viewers to compare the data accurately. Limit the number of chart types: While combo charts can help display multiple data types, it's important not to overload the chart with too many. Generally, limiting the chart to at least two or three chart types is best. Use color and labeling effectively: To help viewers understand the chart, use color and labeling. Use different colors for each chart type to clarify which data points belong to which one. Label each chart type clearly, and include a legend to help viewers understand what each color represents. Choose the proper chart layout: There are different ways to layout a combo chart, such as overlaying the chart types or using multiple axes. Choose the layout that best suits the data you want to display and makes it easy for viewers to understand the relationships between the data points.
Best Practices for Using Stock Charts Use a consistent time frame: When presenting historical stock data, use a consistent time frame throughout the chart. This allows viewers to easily compare trends and patterns over time. Label your axes: Clearly label your chart's x and y axes so that viewers can understand the data. Use descriptive labels that include units of measurement and periods. Avoid clutter: Avoid adding too much information to your stock chart, such as multiple indicators or excessive annotations. This can make the chart difficult to read and understand. Use color strategically: Use color to highlight important data points or trends. However, be careful not to use too many colors or color schemes that are difficult to interpret.	Best Practices for Using Kagi Charts Choose the right time frame: Kagi charts can be used for any time frame, but they are most effective for longer-term trends. Choose a time frame best suits your data and the insights you want to convey. Label your chart: Clearly label your Kagi chart with the asset's name and displayed time frame. This helps viewers understand the data and the context in which it was generated. Avoid over-analyzing: Kagi charts are best used for identifying long-term trends rather than short-term fluctuations. Avoid over-analyzing the chart or trying to make predictions based on short-term movements.	Best Practices for Using Renko Charts Renko charts are a popular technical analysis tool that can give traders a unique way of viewing price action. Here are some best practices for using renko charts effectively: Choose an appropriate brick size: The size should be based on the underlying asset's volatility. A larger brick size will generate fewer signals, but they will be more reliable, while a smaller brick size will generate more signals but may be more prone to false signals. Consider the time frame: Renko charts can be used in any time frame, but traders should be aware that the charts will look different in different time frames. Traders should choose a time frame that matches their trading style and objectives.	Best Practices for Using Point and Figure Charts Determine the box size and reversal criteria. The box size determines the price range of each box on the chart, while the reversal criteria determine when a new column is started on the chart. These parameters are important as they can affect the sensitivity and accuracy of the chart. Use a consistent price scale. Point and Figure charts are not time-based but rather based on price movements. A consistent price scale on the chart is essential for accurate analysis and comparison.	Best Practices for Using a Three Line Break chart Understand the concept: A three-line break chart is based on a series of price movements rather than time. It works by only drawing a new line when the price moves by a certain amount (usually three times the box size) in a certain direction. This helps filter out noise and provide a clearer picture of the trend. Choose the box size carefully: The box size is the amount of price movement required to draw a new line. Choosing the right box size is important as it can affect the clarity of the chart. A larger box size will result in fewer lines and a clearer picture of the overall trend, while a smaller box size will result in more lines and more short-term fluctuations. Combine with other indicators: Three-line break charts can be used in conjunction with other indicators such as moving averages or support and resistance levels to confirm trends or identify potential entry and exit points. Use for medium to long-term analysis: Three-line break charts are best suited for medium to long-term analysis as they can help filter out short-term noise and provide a clearer picture of the overall trend.	Best Practices for Using Vector Charts Ensure data accuracy: Vector charts rely on accurate data points to create accurate representations of your data. Ensure your data is properly collected, processed, and inputted into the chart. Use appropriate scale and units: The scale of your chart should be relevant to the data you are visualizing. It's also important to ensure that the units used to define the magnitude and direction of the data points are consistent and appropriate. Customize the appearance of the chart: Vector charts can be customized to fit the specific needs of your data. Choose arrow styles and colors that work well with your data, and adjust the size and position of the chart as needed. Use labels and annotations: Labels and annotations can be added to a vector chart to provide additional context and make the chart easier to interpret. Consider adding labels to indicate the direction and magnitude of the arrows or annotations to highlight specific data points. Keep it simple: Vector charts can quickly become complex and difficult to interpret. Keep your chart as simple as possible by limiting the number of data points and choosing a straightforward, easy-to-read design.
Best Practices for Using Range Charts Use appropriate data: The Range series is best suited for displaying data defined by two ranges, such as histograms or custom-sized bars. Ensure your data fits this criteria. Choose the appropriate chart type: Nevron Chart component offers a variety of chart types, including 2D and 3D Range charts. Choose the appropriate chart type for your data to ensure it is displayed most effectively. Customize the appearance: Use the range chart's appearance properties to customize the color, border, and shape of your ranges. This can help your data stand out and make it easier to read. Use axis labels and titles: Use axis labels and titles to provide context and make it easier for your audience to understand your data. Ensure that the labels are clearly visible and legible.

Charting Types

Nevron Chart for SSRS provides a complete and unmatched set of 2D/3D charting types and subtypes. Many of the charting types/subtypes that we support are unique within the industry. We support all major charting types and extend all charting types with options that are otherwise not available. Additionally, we provide an option to create truly advanced charting type combinations.

For example: while the default chart report item can display clustered bars, you cannot control the gap between the clusters, nor can you create cluster-stack combinations.

As a total, Nevron supports 174 charting types by counting only the Chart Type/Subtype and availability in 2D/3D combinations - which is an unrivaled industry record.

This number does not include the shape combinations available. For example, the default report item considers Cylinders Columns as a different subtype of the Column chart type - in fact it can display columns only as bars and cylinders. Compare this to the 9 shapes with which you can display columns in Nevron Chart for SSRS.

Also not counted are the possible horizontal charting types that you can author - other currently available charting report items are using different charting types to display either left-to-right or right-to-left horizontal bars. In Nevron Chart any 2D/3D chart can be converted to a horizontal chart in either direction - this includes combo charts too. You should also consider the charts that you can author by creating combo charting types - which in Nevron Chart for SSRS are limitless.

Nevron Chart for SSRS stands in a class of its own when it comes to XY and XYZ scatters of any type and 3D charting.

Advanced Axes Features

Chart axes advanced features

Chart Multiple Axes

Chart reporting services value axis crossing

Chart axis crossing

Chart reporting services axis custom grid lines

Chart axis custom gridlines

Polar chart reporting services clockwise axis angle orientation

Polar and Radar axes

Unquestionably, charting axes are a very important aspect of each chart. Charting axes have to deal with different scaling, labeling, auto show/hide, layout and value/range highlighting features, and provide flexible annotation options that all result in better chart readability. It is safe to say that Nevron Chart for SSRS features one of the most advanced axis models available in charting technology today.

The axes of Nevron Chart can scale all types of axis data - ordinal, hierarchical, numeric, logarithmic, and have the industry-leading support for date-time scales - including value and range timelines scales that are largely used in financial and project management charting. Scaling all types of data is not enough - for each of these distinct types of scales Nevron Chart for SSRS provides advanced and unique options for further tuning. For example: Even though the default chart in SSRS can display hierarchical categorical scale it only supports this in bracket mode - Nevron Chart for SSRS supports three distinct modes for display of such scales with options to control different aspects of the category hierarchy annotation.

Besides scaling, axes have the important role of helping you visually understand the data. Nevron Chart for SSRS supports advanced options for section highlighting, which help you split the axes in visually distinct ranges. Other annotation options include constant lines, stripes, gridlines etc. - all implemented with a wealth of settings. Many of the visual decoration settings are not available in the default chart for SSRS and are generally unique within the industry.

Another important aspect of the visual perception of data is being able to compare it visually. However, when the data is clustered in distant data ranges (for example: half the data points are around 100 and the other half are around 1,000,000) you cannot compare it visually - all small bars will look the same. For the purpose of cases like this, Nevron Chart implements advanced support for manual and automatic scale breaks. Scale breaks are not available in the default chart for SSRS. Chart report items from other vendors that support scale breaks do so only for Y axes in 2D - they do not support scale breaks in 3D, nor do they support axis scale breaks crossing (for example scale breaks that are applied to the X and Y axes of an XY scatter).

Axis positioning is also not left behind. In Nevron Chart for SSRS Cartesian axes can be crossed, docked to chart sides or displayed one above the other. No other report item provides such flexibility in axis positioning - for example many report items can cross the axes at value or percent along another axis, but cannot be docked to the same side (try making the Secondary Y axis appear on the left side docked next to the Primary Y axis - again only Nevron can do this). Another unique feature in axis positioning is the ability to display axes one above the other - for example the Primary Y axis can occupy the bottom part of the chart, while the Secondary Y occupies the top).

To pile the heap of axis features, Nevron Chart for SSRS implements great support for automatic labels arrangement, label value formatting and support for XML formatted titles (see below) that can be aligned and rotated at will. All axis labeling features are crafted to blend with the chart layout - labels and/or chart will grow/shrink to fit perfectly in the available chart area - whatever the data.

3D Charting

Chart reporting services grid surface chart

3D Chart Grid Surface

XYZ Scatter Charts

Chart reporting services trianguated surface chart

Triangulated Surface Charts

XYZ scatter cluster bars

With almost an entire decade of research, Nevron is a leader in 3D charting technology. Nevron Chart for SSRS comes equipped with a fast and robust 3D rendering engine built on top of OpenGL. The 3D charts generated by Nevron Chart for SSRS are unrivaled in image quality, speed, layout, features and consistency aspects.

Nevron is one of few companies that make True 3D charting, and implements it with superb quality and a rich set of features. Most of the other charting engines available today are the so-called 2D-Half engines, which generally use 2D technologies to render 3D charts with smart painting tricks like back-to-front rendering, etc. For example, the default chart for SSRS uses a 2D-Half engine for 3D charting.

All 2D-Half engines, however, remain restricted in the following aspects of 3D charting:

Lighting - the way a 3D chart is lit greatly contributes to the overall image quality of the rendered chart. Nevron Chart for SSRS provides 11 predefined lighting modes and the ability to define custom lighting via code injection (see below).

Materials - no 2D-Half engine supports material specification. Materials are widely used in 3D modeling software to define how objects reflect light - if you want to make some bars shinier or more glittery than others - you can do so by specifying their material.

Texture mapping - all 2D-Half engines suffer texture mapping abilities in 3D. Texture mapping in 3D appears when you want to display a 3D element with gradient, pattern or image filling. For example: you cannot apply gradient filling to a 3D column chart in the default chart for SSRS, but you can apply gradient filling to any element in Nevron Chart for SSRS - in 2D and 3D.

Z-Buffer - 2D-Half engines do not have a Z-buffer - hence hidden surface removal is performed only when possible. A Z-buffer is, however, needed when displaying XYZ scatters, mesh or triangulated surfaces - things that you can easily do only with Nevron Chart for SSRS. The Z-buffer is an indispensable requirement for scientific plots.

Speed - rendering a 3D chart with a 2D rendering engine can be quite slow, especially with thousands of data points. The majority of 2D rendering engines are software engines (use the computer CPU). OpenGL, however, uses hardware acceleration, which transfers rendering to the video board GPU.

Using a 3D engine such as OpenGL is not enough to make quality 3D charting. This is why Nevron spared no efforts to implement lots of shapes (for bars, pies, points etc.), enforce perfect chart layout in 3D, ensure that 2D and 3D features behave consistently, and increase the readability of 3D charts in general.

If you need quality 3D charting - look no further.

2D Charting

Although Nevron became popular with the quality 3D charts that it develops, the 2D charting abilities of Nevron Chart for SSRS are just as impressive.

Besides implementing all chart related features required to produce quality charts in 2D, Nevron Chart for SSRS adds the industry unique support for image filter effects - bevel and emboss, glow, lighting etc. Simply put, no other charting engine can produce charts with better looks.

Image filters help you create pixel perfect charts, only comparable to charts that professional designers can produce with Adobe Photoshop after countless hours of work.

In Nevron Chart for SSRS image filters can be applied to all chart elements including texts in 2D and to all texts in 3D. Image filters are also used internally in shadows and that is why Nevron Chart for SSRS is the only chart that can display soft shadows with pixel perfect quality.

2D/3D Consistency

Nevron Chart for Reporting Services is consistent in 2D/3D modes. For example, you can map gradients, textures to elements in both 2D and 3D. Colors specified in 2D are inherited by materials in 3D. You can mix 2D and 3D chart areas in a single chart control.

Forward / Backward Compatibility

Nevron Chart for SSRS 2005/2008/2008R2/2012/2014 is forward and backward compatible. This means that charts created in SSRS 2005 can be used in SSRS 2008, 2008R2, 2012 or 2014 and vice versa.

The forward/backward compatibility ensures chart design reuse not only when migrating from one edition of SSRS to another, but also when sharing chart designs between departments possibly using different versions of reporting services.

Chart Templates

Chart Templates

Nevron Chart for Reporting Services allows saving and loading XML templates for appearance settings. This is very helpful in order to accelerate time needed to produce consistent charts and charts with company brand styling.

The state generated by the VS2005 and VS2008 report items is compatible, meaning you can easily convert reports generated with different versions of Visual Studio. The embedded styling support allows you to quickly apply color palettes in order to change the appearance of the chart contents. In addition, you can create your own, custom set of palettes to further accelerate the authoring of company branded charts.

Visual Editors

Chart Designer

Nevron Chart for SSRS provides numerous editors, allowing you to easily modify the chart appearance and customize all elements of your charts - quickly and completely visually. Changes that you make to the chart are previewed in real time so that you can instantly see the effect of your settings.

We spared no effort in making the Chart Designer truly improve your report authoring experience. That is why we had to make it multithreaded. You may have noticed that other chart report items for SSRS are edited very slowly and not all changes that you make are instantly previewed. A common limitation of single threaded chart designers (currently all others) is that you cannot make instantly previewed changes very quickly. This is because a single threaded designer will block your UI on preview update and leave it unresponsive. The Nevron Chart Designer is multithreaded - the more cores you have finally matter - it loads blazingly fast and chart customization becomes a real pleasure.

Code Embedding

Chart Code Customization

Nevron Chart for SSRS supports customization through C# code, allowing users with development experience to further customize the chart using the full Nevron Chart for .NET API inside SSRS.

Although Nevron Chart for SSRS already exposes a vast amount of settings, the Nevron Chart engine beneath it has even more. If you cannot do something with the settings already exposed - ask us - it may be doable with code.

This is a truly great and rare feature that helps you standardize on Nevron Charting technology at all levels in your company - from developers to IT professionals.

Rich Texts and Texts Quality

Nevron Chart for SSRS is not just great in displaying charts - it is great in displaying texts too. It features the unique XML formatted texts feature, which lets you create titles, labels, headers, footers etc. with rich texts formatting.

XML formatted texts use a format similar to HTML, which lets you mix fonts, subscript and superscript, bold, italic, underline formatting and - as you would expect from Nevron - advanced features like different fill styles, borders, shadows, image filters etc. – all inside a single label, title etc.

This helps you display certain mathematical formulas, which would otherwise not be possible. It also helps you replicate nicely titled charts that you can otherwise only see in print magazines (by the way, many print magazines already use Nevron Chart for .NET).

Supported and Documented

We take great pride in the quality of our support, which is provided by the people who developed this solution for you. You do not need to be an expert in charts and reporting, because we already are and we are here to help you.

The documentation of Nevron Chart for SSRS is also very thorough, complete and straight forward.

Constantly Enhanced

Nevron Chart for SSRS is a product that is constantly enhanced with new features added at each volume release. You can be sure that we will make everything possible to satisfy all your advanced charting needs.

Additional Features

Except the many advantages and customization options already mentioned, Nevron Chart for SSRS offers great number of additional features such as:

Chart Walls and Legends customization
Per Series values Data Groupings
Data Grouping Editors
Control over the Rendering Properties
Pie Chart Non-Overlapping Labels
Nevron Pie Chart Non-Overlapping Labels mode solves the labels overlapping issue, caused by small pie segments or in cases where there are many pie slices - the Spider Non-Overlapping labels mode is similar to the Spider mode, however the pie chart labels are automatically positioned in a manner that doesn't allow them to overlap with each other.

and more...

Pricing and Licensing

Nevron Chart for SSRS offers a simple and cost-effective licensing model. It is an affordable solution, bringing to your reports the most advanced charting engine available today. The Chart for SSRS is licensed per designer and report server, there is no restriction on the number of CPUs the server has. In terms of ROI, it is simply unmatched.

Conclusion

We hope that this document gives you more than one reason why you should be on the board of the most advanced charting technology available in SSRS today. Do not take our word for granted - download the evaluation now and see for yourself how we can chart your data.

About Nevron Software

Founded in 1998, Nevron Software is a component vendor specialized in the development of premium presentation layer solutions for .NET based technologies. Today Nevron has established itself as the trusted partner worldwide for use in .NET LOB applications, SharePoint portals and Reporting solutions. Nevron technology is used by many Fortune 500 companies, large financial institutions, global IT consultancies, academic institutions, governments and non-profits.
For more information, visit: www.nevron.com.

Customer Quotes

We needed a solution that could produce a bar graph with overlaid SEM bars. After some research, we determined that Nevron Chart for SSRS component was the right fit, allowing us to easily produce a graph such as this.

Nevron has been very helpful and responsive to our needs. We are pleased with the product and hope to expand its use in our systems in the future.

.NET Components

BI and Reporting Tools

.NET Components

BI and Reporting Tools

.NET Components

BI and Reporting Tools

Additional Resources

Why Choose Nevron Chart for SSRS?

Why Choose Nevron Chart for SQL Server Reporting Services?

Charting Types

Best Practices for Using Bar Charts

Best Practices for Using Pie Charts

Best Practices for Using Line Charts

Best Practices for Using Area Charts

Best Practices for Using Line Charts

Best Practices for Using Point Charts

Best Practices for Using Bubble Charts

Best Practices for Using Surface Charts

Best Practices for Using Mesh Surface Charts

Best Practices for Using Triangulated Surface Charts

Best Practices for Using Vertex Surface Charts

Best Practices for Using Radar Charts

Best Practices for Using a Polar Chart

Best Practices for Using High-Low Charts

Best Practices for Using Error Bar Charts

Best Practices for Using Funnel Charts

Best Practices for Using Box and Whiskers Charts

Best Practices for Using Combo Charts

Best Practices for Using Stock Charts

Best Practices for Using Kagi Charts

Best Practices for Using Renko Charts

Best Practices for Using Point and Figure Charts

Best Practices for Using a Three Line Break chart

Best Practices for Using Vector Charts

Best Practices for Using Range Charts

Charting Types

Advanced Axes Features

Chart axes advanced features

Chart Multiple Axes

Chart axis crossing

Chart axis custom gridlines

Polar and Radar axes

3D Charting

3D Chart Grid Surface

XYZ Scatter Charts

Triangulated Surface Charts

XYZ scatter cluster bars

2D Charting

2D/3D Consistency

Forward / Backward Compatibility

Chart Templates

Chart Templates

Visual Editors

Chart Designer

Code Embedding

Chart Code Customization

Rich Texts and Texts Quality

Supported and Documented

Constantly Enhanced

Additional Features

Pricing and Licensing

Conclusion

About Nevron Software

Customer Quotes

David Miller, Manager Software Development Medical Council of Canada

Next Steps

David Miller, Manager Software Development
Medical Council of Canada