Your business operations need better data visualization. What tools can help you succeed?

Interactive dashboard by processing of raw data to provide business and clients' trends and behaviour to make forecasting and support the decisions making Also for monitoring of decreased business to analyse the root cause It's really useful for the cross selling as well

Data visualization is crucial for informed decision-making, problem-solving, and process optimization in business operations. Through charts, graphs, maps, dashboards, and other visual elements, raw data can be translated into compelling stories that inform and inspire. Visualization helps in monitoring key performance indicators (KPIs), identifying gaps, tracking progress, and fostering a data-driven culture. It enables widespread access to data, ensuring that everyone in the organization can understand and leverage it to enhance their work.

Leaders and decisions makers are inundated with an overwhelming amount of data that they simply do not have enough time to analyze and interpret. Data visualizations make the trends and insights hidden in large data sets easy to understand in a short amount of time. Analyst put in the hard work of analyzing data, but easily summarize 8 hours of analysis into a visual that only takes 5 seconds to understand. Hence, data visualization is essential in efficiently communicating the insights found in organizational data. Without simple tools like bar graphs and pie charts, it becomes difficult to intuitively understand what data may be indicating.

We live in data driven society and data driven culture in the organization is imperative to sustain and survive businesses. Data visualization helps in data driven culture and simplify the process of convying as well understanding which overall boosts improvement in the business proceesses.Visualization makes data driven analytics are extremely useful in making informed business decisions.

For businesses to succeed, it is necessary to understand what are the key metrics which define success. We need to understand where we stand with those metrics and what should be the end goals. Visualization plays a key role in achieving these. Visualization helps in consolidating data from multiple sources and provides single source of truth for end users. It handles huge amounts of data which cannot be handled by excel

Use of data visualization tools depends upon the purpose for which tool is required. What is proposed to achived via use of visualization is essential to decide first. Depending upon need choose the data visualization tool.

Choosing a data visualization tool requires considering factors like data type, source, purpose, audience, cost, and complexity. Ensure the tool can handle your data's volume, variety, and velocity while creating suitable visualizations. Look for customization options in design, layout, and interactivity to align with your audience's preferences. Consider factors like budget, skill level, and available support when choosing tools like Tableau, Power BI, Google Data Studio, or D3.js. Each tool has its strengths and weaknesses, so thorough research is crucial before making a decision.

Ad-hoc visualization can easily be accomplished with Excel or Google Sheets, with Excel having noticeably superior customization capabilities compared to Google Sheets. Charts from these tools can easily be incorporated into their respective slideshow presenting software for professional presentation. For more advanced data visualizations using large data sets or for dashboards with real-time data, you'll need to use a true BI intelligence tool. An easy place to start for enterprise data is Google LookerStudio which is 100% free and directly integrates to tons of common tools. If you're a serious data analyst, you'll be looking to tools like Microsoft's Power BI or Salesforce's Tableau.

There are many tools available in the market, but it largely depends upon the organisation’s requirement, size of the business, budget and Infrastructure for deploying any visualisation tools.

We normally use power bi for almost all kinds of visualizations. It is working flawlessly and is easier to get on board with. Recently, I was on call with a co worker from a different continent and he was telling me about his excel file which makes it easier for him to track and manage inventories by making important bits easier to view at a glance. I requested him to ask me any question about his inventory and I showed him how Power bi can help him answer in way less time than updating a clunky sheet. He was hooked!

Effective data visualizations result from thoughtful design principles. - Start by clarifying your goal, question, and audience. - Choose a visualization type aligned with your data and message, adhering to basic rules. - Utilize suitable colors, fonts, labels, legends, scales, and axes, avoiding misleading elements like 3D effects, pie charts, or truncated axes. - Always cite data sources, and offer context and explanations to enhance understanding. This will ensure that your visualizations are not only visually appealing but also accurate and meaningful.

Simplify and declutter: Keep the visualization simple and avoid clutter. Remove unnecessary elements, labels, or decorations that do not contribute to the understanding of the data. Use whitespace effectively to provide visual separation and enhance clarity.

Sharing data visualizations can be done in a few ways. When I don't want someone to be able to access the data I will generally package up Excel Pivot Charts onto a single page, and publish a PDF that can be easily distributed. The benefit here is that your team only needs to see the output, and not all of the inputs, which simplifies things for them. If I don't mind someone having access to the data, I will invite people to a shared Excel document with the Pivot Charts. However, you must consider that someone could destroy your data if they are not careful. You may also use Tableau, or Microsoft Power BI to visualize electronic data easily. However, Tableau doesn't give you the same level of control as Excel does.

Sharing data visualisation should depends on the recipient audience and the frequency of the reports. For leadership power point can be suitable provided amount of data is less. If we have large dataset then it's good to use tools like Tableau & Amazon QuickSight which have ability to process large dataset, and these tools provide features to schedule reports for the recipient in a customized manner which will be auto sent based on the frequency selected.

The messages are clear and consistent. The approach is applicable for such different companies and areas. Data visualization is a key element to engage people on data analytics.

Before getting started user should be aware of the data volume and the type of data is available. Most of the tools support structure data(RDBMS) for visualisation and very less tool have capability to support unstructured data(Excel or any text file) so if you are dealing both then you need to know a way where you can convert the unstructured data stream to structured data and inject in the visualisation.

CARRIES HIGH VOLUME PRECISION DATA: Data visualization tools handle are like libraries and business intelligence outfits which help businesses to succeed.They are capable of handling large files,and simplifying such data. Some of the best data ,visualization tools include Google Charts, Chart Blocks,and Tableau, etc . These tools analyses high volume data,give clearer information of the data, processes the data,gives a clearer presentation and results. The operational outcome of the results are very specific, measurable, within a reasonable time.