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Data Visualization Cloud

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Last Updated: 02 July 2021

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General | Latest Info

Advance / Newhouse has decided to acquire Big Data Analytics company 1010data for $500M. 1010data facilitates Big Data discovery and data sharing by means of a spreadsheet - like interface. The platform boasts Predictive Analytics, reporting and visualization as well as solutions for data sharing and monetization. 1010data Management team will lead the company but new capital will be used to accelerate product development and expand sales operations. 1010 Platform gained initial traction in the financial services industry but has subsequently expanded to a customer roster of over 750 companies that also includes retail, gaming, telecommunication and manufacturing. 1010datas acquisition by Advance / Newhouse illustrates the vitality of market interest in Big Data discovery and data visualization solutions. Advance / Newhouse solutions is the parent company of Conde Nast magazines and Bright House Networks. Datahero today announced finalization of $6. 1m in Series funding led by existing investor Foundry Group. Funding raise will be used to scale companies ' operations in anticipation of rapid growth and customer demand for its Cloud business intelligence solution. As told to Cloud Computing Today in a phone interview with DataHero founder Chris Neumann, DataHero gives organizations capability to rapidly visualize Data in structured and semi - structure forms by means of Cloud - base Platform that accepts intake of Data in CSV, Excel or integrations with select third party data feeds. For example, customers can load one or more Excel files into DataHeros business intelligence Platform to visualize, transform and perform drill - downs on data. Datahero Platform features connectors to a range of third party platforms that include Marketo, HubSpot, Salesforce, Zendesk, Google Analytics and Cloud storage platforms such as Box, Dropbox and Google Drive. In comparison to other data visualization platforms, DataHero focuses on non - technical end users that need to streamline and simplify path toward visualizing larger significance of data of interest. Today, DataHero also revealed the appointment of serial entrepreneur Ed Miller as CEO. Miller has led a number of tech startups and his appointment underscores both DataHeros's historical growth as well as the urgency of its plans to gear up for the next phase of its evolution. Expect DataHero to continue expanding the roster of platforms with which IT integrates and deepening its analytic capabilities as IT continues to deliver on its sweet spot of visualizing and presenting data to end users in ways that empower business stakeholders to make more convincing cases for their business decisions using Data present in compelling and palatable forms. Wire Data Analytics leader ExtraHop and Machine Data Analytics vendor Sumo Logic recently announced a partnership whereby ExtraHops wire Data will complement Machine Data aggregate by Sumo Logics Cloud Platform. The partnership brings together ExtraHops leadership in wire Data Analytics and Sumo Logics recognize Machine Data Analytics Platform to create a unified framework for event detection and Management. As result of collaboration, ExtraHops Open Data Stream delivers real - time, streaming feeds of wire Data to Sumo Logics Platform for aggregating and analyzing Machine Data.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

What Is Data Visualization?

In short, data visualization is visual depiction of information. It is imagery dedicated exclusively to messaging or presenting information. Data visualization tools can automatically create visualizations, enable you to create your own, or offer both capabilities. At the lower end are simpler and even free data visualization tools are dedicated to building infographics rather than performing sophisticated Data Analytics. Some of these tools include Tableau Gallery and even Microsoft Power BI. In January 2018, Tableau introduced a new data engine called Hyper that the company claims gives users up to five times faster querying speed over previous versions. Meanwhile, in July 2018, Microsoft rolled out new features for Microsoft Power BI, such as integration of Big Data directly into Power BI web service. At the higher end are tools that can change visualizations on the fly, in the same way that output from sophisticated algorithms changes after repeating direct querying of real - time data and across multiple data sources. Tools occupying the middle of the spectrum do not represent real - time data but still produce visualizations from Advanced Analytics outputs. Self - service BI apps we review contain average to higher - end visualization tools. Some of tools contain strong natural Language Query capabilities like Sisense, and others bring real - time Analytics for Internet of Things, like SAP Analytics Cloud. In short, you cannot judge the quality of the underlying Analytics engine by the cover of its art package. Some very powerful Analytics come with pitiful passing visualization capabilities. Conversely, some pitiful passing Analytics come with some pretty impressive visualization features. Since we originally reviewed these BI tools, IBM has discontinued offering IBM Watson Analytics for purchase. Instead, IBM introduced Cognos Analytics 11. 1, which offers guided data discovery, automated predictive Analytics, and the ability to interact with data conversationally. There is a wide range of art depictions that data visualization tools can create. Some depictions are simple, some are complicate. Some are beautiful, some are crude. And there are some that are truly individual creations. But most spring from templates in traditional forms associated with statistics. The simplest examples of data visualization are pie and bar charts you 've been able to access via Microsoft Excel for many years now. But as BI has matured as a platform, so, too, have options available to you for seeing your data and presenting it to others. Tools we review here reflect the medium to higher end of the spectrum in BI; they re capable of performing sophisticated queries without the need to understand Structured Query Language coding. Plus, they can render Analytics in a wide variety of visual formatsgoing far beyond basic bar Chart to include geographical mapping, heat maps, sparklines, and even more specialized visualizations such as the spider Chart below. Data visualization is not a new concept. Pie Charts and bar and line graphs have existed throughout the ages. What's changed are the kinds and size of data that can be represented this way, and many more sophisticated ways in which you can show it and share it.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

The Importance of the Dashboard

Business questions dashboard answers depend on industry, department, process and position. Analytical dashboards are typically designed to help decision makers, executives and senior leaders, establish targets, set goals and understand what and why something happen with the same information they can use to implement appropriate changes. Analytical dashboards do this based on insights from data collected over a period of time determined by user. Data is visualized on dashboard as tables, line charts, bar charts and gauges so that users can track the health of their business against benchmarks and goals. Data dashboards surface necessary data to understand, monitor and improve your business through visual representations. Depending on how you decide to design your dashboard, even straightforward numerical data can be visually informative by utilizing intuitive symbols, such as red triangle facing downward to indicate a drop in revenue or green triangle facing up to indicate an increase in website traffic. According to Wikipedia: Analytics is discovery, interpretation, and communication of meaningful patterns in data. Especially valuable in areas rich with recorded information, Analytics relies on simultaneous application of statistics, computer programming and operations research to quantify performance. Analytics often favors data visualization to communicate insight. Dashboards are data visualization tools that allow all users to understand Analytics that matter to their business, department or project. Even for non - technical users, dashboards allow them to participate and understand the Analytics processes by compiling data and visualizing trends and occurrences. Data dashboards provide an objective view of performance metrics and serve as an effective foundation for further dialogue. Dashboard is a business intelligence tool used to display data visualizations in a way that is immediately understood. Most businesses use multiple services to track KPIs and metrics, which take up time and resources to properly monitor and analyze. Dashboards use raw data from these sources, spreadsheets and databases to create tables, line charts, bar charts and gauges on a central dashboard that users can look at and immediately understand key metrics they are looking for. Data dashboards simplify end of month reporting by allowing users to communicate information at any time without hours of preparation and analyzing. Changes to any aspect of business, whether IT be in marketing, sales, support, or finance, have an impact on business as a whole. People have been monitoring their businesses without dashboards for ages, Data dashboards make IT a heck of lot easier. With dashboards, users are able to dig deeper into the big picture to correlate this impact alongside specific KPIs and metrics to understand what works and what does. Whether your business data is stored on web service, attachment or API, dashboard pulls this information and allows you to monitor all your data in one central location. Additionally, dashboards are capable of correlating data from different sources into single visualization if the user so chooses. By monitoring multiple KPIs and metrics on one central dashboard, users can make adjustments to their business practices in real time.


What Is Data Visualization?

The purpose of Data Visualization is pretty clear. It is to make sense of data and use information for organizations ' benefits. That say, data is complicate, and it gains more value as and when it get visualize. Without Visualization, it is challenging to quickly communicate data findings and identify patterns to pull insights and interact with data seamlessly. Data scientists can find patterns or errors without visualization. However, it is crucial to communicate data findings and identify critical information from them. And of this, interactive Data Visualization tools make all the difference. Relevant and recent example is the ongoing pandemic. Yes, data scientists can look into data and gain insights. But Data Visualization assists experts in staying informed and calm with such an abundance of data.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

What to Look For

Ultimately, data visualization capabilities are used to build dashboards. Sometimes the dashboard represents a single, data - base story that is significant to many viewers. Or dashboard may contain many stories for the benefit of single user. Dashboards sometimes come with visualizations that are preset and fixed in place. Other times, dashboard visualizations come with various display options or images that are customizable. Sharing can often be customized too, such as according to permissions, per business line, per job role pertinence, or even by personal preferences. In any case, dashboards typically contain two or more data visualizations meant to inform and sometimes even prompt business action or decision. Prior to the advent of self - service BI tools, executives had to present their questions to database professionals who would then try to understand IT as best he or she could, write SQL query, and represent that question against database or data warehouse. The result would be fed to an IT person who would then write necessary code to represent IT as dashboard on the executive's team website, on share app, or even just as standalone document executives receive via email. If more than one data source was needed, then very often more than one database professional had to write separate queries. At the end of this inefficient and multistep process were analyses. You get historical analyses. These reports usually arrive too late for business to change or influence the outcome of activity IT depict. Thus, business analysts, department heads, and C - suite leaders typically receive reports with delayed, overly simplistic, and vague information. Sometimes information was irrelevant when IT finally made its way to business analysts or C - suite because the company had changed direction or other factors emerged in the meantime. Even so, dashboards and reports made in this way rarely change. Things proceed as they always had: same questions ask, same data query, same reports and dashboards generatedday after day and week after week. By contrast, today's self - service BI apps let business analysts bypass middlemen and unstop many IT bottleneck. This self - service software also enables use of data outside company as well as from within, such as social media, Cloud, public data sets, and IoT Data. Some self - service BI apps can use real - time data, but many are limited to near - time data. However, near - time data usually isn't business limitation. There are actually only a few cases where real - time data analysis warrants extra effort and expense. After all, near - time refreshes can be as frequent as every minute or less. With regards to self - service BI dashboards, key value is typically threefold: first, they don't require database expertise to use. You 'll probably need your database professional's help to set them up and connect them to all of the data sources you need. After all, compliance and security issues still remain.


What Is Data Visualization?

Effective visualization do lot more than just display data set. It creates a narrative, providing clear answer to specific question, minus minutiae. The end goal is to educate and engage your audience with your insights. Were all up to our eyeballs in information, and the ability to leverage data to tell a story is an increasingly important skill. Whether you are communicating findings of your customer survey, making a presentation to the board, or simply engaging your target audience, your success or failure all comes down to your mastery of data storytelling. Data visualization serves as one of the most critical tools in your storytelling arsenal. It helps to reimagine Business Intelligence and introduces organizations to new ways of understanding and utilizing their data. Emerging as a critical foundation for democratizing data and making intelligent insights available to everyone within the organization, modern data visualization tools empower users, reduce dependence on overburdened IT departments, and help to drive businesses forward.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

Tableau Public

Our goal as Data Analysts is to arrange insights of our data in such a way that everybody who sees them is able to understand their implications and how to act on them clearly. Tableau is a data analytics and visualization tool used in the industry today. Many businesses even consider it indispensable for data - science - related work. Tableaus ease of use comes from the fact that it has a drag and drop interface. This feature helps to perform tasks like sorting, comparing and analyzing, very easily and fast. Tableau is also compatible with multiple sources, including Excel, SQL Server, and cloud - base Data repositories, which make it an excellent choice for Data Scientists.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

Highcharts Cloud

Chart Types: General and interactive. Difficulty: Open to everyone. Cost: Free. Highcharts Cloud is one of the easiest to use data visualization tools, and it still looks really good too. This is a free solution offered by Highcharts who have a load of other visualization products you can find here. The tool has your general charts, while all you need to do is enter some data and youll have nice, clean visualization. The downside is that there isnt much customization here. Youre quite limit on what chart will look like and how data is display. But if youre after quick and simple visualization, you dont need to worry about that anyway.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

D3.js

Chart Types: General, Interactive, maps, scientific, mathematical, and technical. Difficulty: Youll need a developer for this. Cost: Free. D3. Js isnt tool such, it is a JavaScript library that is used to create data visualizations. This means youre going to need someone with some ability ability to help you out if it is beyond your own skills. D3. Js is incredibly powerful and versatile though, so it is worth effort to get to grips with. There are a number of tutorials out there to help you as well. In regards to what you can do, options are massive. As it is all done through coding, you do have to worry about restrictions that other tools have. It does everything from basic line charts to entirely unique and obscure visualizations you might not have even heard of. The best bet is to check out examples here to see what is possible.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

FusionCharts

The best data visualization tools include Google Charts, Tableau, Grafana, chartist. Js, FusionCharts, Datawrapper, Infogram, ChartBlocks, and D3. Js. The best tools offer a variety of visualization styles, are easy to use, and can handle large data sets. Data visualization Tools provide designers with an easier way to create visual representations of large data sets. When dealing with data sets that include hundreds of thousands or millions of data points, automating the process of creating visualization makes designers ' job significantly easier. Data visualization techniques include charts, plots, diagrams, maps, and matrices. There are many variations on these specific techniques that designers can use to meet specific visualization needs based on data theyre working with. Large data sets with thousands or millions of data points are almost impossible to discern usable information or draw conclusions from unless some kind of visualization is employ, whether its basic graph or interactive data visualization dashboard. Without data visualizations, drawing conclusions from large data sets or even discerning usable information from them is almost impossible. Using data visualization methods, designers can make information understandable for stakeholders.


Conclusion

There is such a huge variety of visualization tools available to designers that it can be hard to decide which one to use. Data visualization designers should keep in mind things like ease of use and whether tool has features they need. Selecting the most powerful tool available isnt always the best idea: Learning curves can be steep, requiring more resources to just get up and running, while simpler tool might be able to create exactly what is needed in a fraction of time. Remember, though, that tool is only part of the equation in creating data visualization; designers also need to consider what else goes into making great data visualization. Most data visualization tools include free trials, so it is worth taking time to try out a few before deciding on a single solution.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

Carto

Chart Types: Interactive Maps with some in - chart functionality for histograms. Difficulty: take a bit of practice. Cost: Free with pay plans to unlock more features and data. If youre after Interactive Maps, CARTO is probably the best tool out there. Use for Location Intelligence and and journalism alike, you can create some impressive maps without much technical knowhow. In - build wizard means you can create some sophisticated stuff without writing a line of code. It will take some getting used to though, particularly in regards to some file formats you might not be familiar with. Working with Dev will make CARTO less restrictive and more powerful, so it is worth looking into that. Otherwise, spend a bit of time reading up and playing around and youll get the hang of it pretty quick.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

QGIS

With recent advancements in LIDAR survey technology and photogrammetry, there has been huge demand for capturing and storing Point Cloud Data. Point Cloud Data are vector in nature, but are usually orders of magnitude larger than standard vector layer. Typical vector datasets range from thousands to millions of features, while point clouds range from millions to billions or even trillions of points. Due to this sheer number of points, completely different approach to visualise, analyse and storing point clouds is needed in the GIS platform. Integrating Point Cloud viewer in desktop GIS application Add lot of value for users compared to specialise and dedicated Point Cloud viewer: Point Cloud Data can be visualise, compare, and analyse alongside other types of spatial Data familiar User interface and workflows Integration with analytical tools to quickly Create derive datasets despite these benefits, current versions Of QGIS desktop application do not Support visualisation Of Point Cloud Data. With our partners at Lutra Consulting and Hobu, we have decided to bridge this missing gap and add Point Cloud Support to QGIS, and are launching a new crowdfunding campaign to fund this work! Head on over to the official crowd funding page here for full details of the campaign, and for details on how you can contribute and make this work a reality.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

Datawrapper

Parametrically search and Cross - reference 1 billion electronic components, including semiconductors, passives, and electromechanical components using partial or complete part numbers search. Select relevant attributes on all product types for hundreds of categories. Review historical datasheets and PCNs available on your components. Gain in - depth look into electronic component lifecycle status Compliance Data, alternatives, and proactively manage obsolescence, available, environmental Compliance Data, with future benefits by knowing forecasted lifecycle for components. Obtain comprehensive data on current environmental regulations such as REACH and RoHS directives, including full material Declarations. Years to end of life forecasts are calculated using Advanced lifecycle algorithms, allowing users to make better component selection decisions. Certificates of Compliance, material Declarations, and Product Change Notifications are also associated at part number level. Bom Grading offers automated part recommendations to effectively improve BOM grades and increase productivity. Each part indicating high risk is paired with recommendations for alternate parts to increase the health of BOM. Users can enhance productivity by solving significant issues and showing multi - sourcing options in one single view, eliminating the need for multiple Excel Sheets. Customizable to specific company need,sss advanced Risk reporting feature creates easily shared and exportable risk reports. The Siliconexperts Compliance Module enables users to manage environmental and supply chain Compliance requirements. Modules cover chemical regulations ranging from EU REACH and RoHS, Prop65 to conflict minerals and much more. Companies can leverage tools within the P Platform to automate their supply chain data collection efforts as well as build customer and regulatory reporting forms to meet customer requests. The solution is fully Enterprise integrate, enabling transparent synchronization of BOM and material data and supports major PLM / ERP systems on market. Siliconexpert actively monitors more than 20 regulations to ensure the P Platform is always current to reflect today's regulatory landscape and scales to meet tomorrow's challenges and rule changes.


Best Data Visualization Tools

Sisense takes a different approach to business intelligence than the rest of the tools on this list. Their platform is built specifically for developers and engineers to use within their own custom applications. So, if youre interested in creating Analytic apps and can afford the big - business price tag, this is an excellent Enterprise option. With Sisense, you can embed custom data visualizations anywhere using live and cache data to build optimized analytic applications for your team or someone else. You can use this tool to create Interactive dashboards, Self - service Analytics, or white - label business intelligence apps to suit your specific needs. Custom UI to deliver brand Analytic experiences Sample application to test - drive your UI designs dedicate portal for developer content Self - service dashboards AI Data trends It is hard to go wrong with customer base, including those like NBC, Wix, and Rolls Royce. And they are known for having the best customer service in the industry. Plus, you can choose between on - premise, cloud - base, Linux / Windows, or hybrid deployment. However, pricing isnt available online since every plan is custom to fit your situation. So head over to their pricing page to request a free quote or browse through their detailed use - case examples.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

Sources

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

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