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This year’s Business Intelligence Software Product of the Year contest was a sack race between apples and oranges, with the top three finishers representing very different products with diverse functionalities. Yet the results provide a snapshot, however fleeting, of what IT managers consider important now: integrating data across the enterprise, managing cost and maximizing value for the end-user.

“Companies are accumulating a lot of data every day from various departments across the enterprise and many of them are not sure what to do with it,” says IDC analyst Dan Vesset in Framingham, Mass.

The need for answers to this business dilemma is fueling growth in the business intelligence tools market, which Vesset expects to swell to $9 billion in 2005, a 28% surge over 2000. End-user query and reporting and online analytical processing (OLAP) will drive much of that growth, he believes, capturing a combined 79% of the business intelligence tools market by 2005.

The top two finishers — Microsoft Corp.’s Data Analyzer and Business Objects’ Application Foundation, with 24% and 19% respectively of the 178 votes cast in this category — represent generic tools that can be used to query and analyze customer and sales data. By contrast, third-place winner Cognos Finance 5.1, with 12% of the votes, is a more specialized application for financial analytics and budgeting.

In part, the timing of the contest accounts for these results. It’s no wonder that, with budgets on the brain in December, IT managers voted Cognos’ relatively obscure finance product into the top three. And, like a film released in December and therefore top-of-mind at Oscar time, the novelty of Microsoft’s Data Analyzer — launched just last November — may in part account for its first-place finish.

Ultimately, however, Data Analyzer pulled into first place because it does something IT execs love: makes end-users happy at a price that brings a smile to the face of senior management.

The stand-alone Office product brings basic intelligence to the masses, allowing anyone in the company with Windows on their desktop to access data and analyze it by creating charts, graphs and reports that can be saved directly to Excel and Powerpoint. And, at a retail cost of about $179 per user per year, the price is unbeatable. Data Analyzer may not be the most sophisticated solution out there, but it sure makes the IT department look good.

Consider the case of Toronto-based Novopharm Limited, a company that provides generic drugs and products to Canadian pharmacies. Founded in 1965, the company employs about 900 people and was recently acquired by Teva Pharmaceutical Industries Ltd. of Jerusalem, Israel.

Novopharm was spending way too much time querying backend systems to understand customers and products, says Doug Morley, manager, sales administration. Sales reps were constantly calling the busy information systems team to source the latest statistics and data-and could never be sure if the information was complete and up-to-date.

“If I told a manager to report on all the factors affecting his business by key customers and products, it would have taken him days to complete a number of data runs and specialized reports ” and then hopefully come up with the right answer, Morley says. “We had to find a way to pull up accurate data at the front end and put it into a usable, easily accessible and intuitive format.”

Working with a local business intelligence and CRM solutions provider, Novopharm settled on a Microsoft solution: after all, they already had Windows, Excel and Powerpoint on every machine. They used an SQL server for compiling data and worked with their vendor to create data cubes that reflected their business processes. The data cubes-and Microsoft Data Analyzer-were then loaded onto every client, putting pertinent information directly into the hands of users-fast. Just two people were able to bring the solution live in two months.

According to Morley, Novopharm has been able to increase its market share, approach customers in a more educated fashion and develop new selling strategies-all of which contribute to the bottom line.

For high-level users, Data Analyzer may not be robust enough to handle sophisticated queries — something Microsoft readily admits.

“Data Analyzer is not the be-all and end-all of BI,” says Francois Ajenstat, technical product manager for Microsoft Office. “It’s aimed at the mid-range non-technical user, the casual data analyzer who spends at most an hour a week crunching numbers.”

The company has scored a hit by targeting a broader range of decision-makers within organizations already plugged into Microsoft. The interface is integrated with the Microsoft SQL server database and makes use of its OLAP server, although it also works with Sybase, DB2 and Oracle. The system requires a 300 MHz Pentium III processor and 128 Megabytes of memory.

Voters had a choice of the following nominees:

Brio Software Inc.

Business Objects

Cognos Inc.

Actuate Corp.

Microsoft Corp.

Microstrategy Inc.

Teradata, a division of NCR Corp.

Information Builders

Larger companies, such as PDI, Inc., a pharmaceutical marketer with over 3,500 reps in the field, may need more customized solutions that go beyond the capabilities of Microsoft’s server and Data Analyzer.

“We need business intelligence not just for sales and incentive compensation data, but also for data warehousing, operations and marketing analytics,” says John Hollier, PDI’s vice president of technology in Upper Saddle River, N.J. Hollier is implementing the company’s knowledge management strategy in phases, starting by rolling out a Siebel sales automation platform this year.

Whether a company is large or small, however, the goal is the same: make the data work to boost your bottom line. Going forward, IDC’s Vesset predicts even greater sophistication in end-user delivery and analytics: products that support business intelligence via PDA, phone and other mobile devices.

Ultimately, it’s not the technology that will hold companies back, he says, but a willingness to break down barriers between business units, share information across the enterprise and push valuable news-you-can-use out to decisionmakers fast.

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19 Top Platforms For Analytics And Business Intelligence (Business Intelligence And Analytics)

Analytics refers to the use of mathematics, machine learning, and statistics to derive insightful patterns and knowledge through precedent data. With the power of analytics,

What is Business Intelligence?

Business intelligence translates to architectures, processes, and technologies that help convert the great amount of raw data into relevant and meaningful information that can prove conducive to business to derive actionable insights to improve and optimize processes. Why do you need a platform for analytics and business intelligence?

Business analytics is gaining a fair share of impetus as more enterprises understand the need to incorporate it into the system. However, the businesses are on a quest to find the right analytic tools such that they come easy to use by every employee in the organization.

With the help of these tools, the employees will be able to gain real-time insights without really having the technical expertise to spend time analyzing everything by themselves.

Let us have a look at some of these platforms that come handy for analytics and business intelligence, to make the processes all the more smooth, efficient, and optimized.

20 Top Platforms For Analytics And Business Intelligence (Business Intelligence And Analytics) 1. Tableau 

Tableau is one of the best in class, a self-service analytics platform that performs amazing visualizations of data.

Easy comprehension – The visualizations are understandable with the help of color, cartography, and animation. After all, isn’t its simplicity and easy comprehension that firms look for when it comes to analytics?

2. Oracle analytics server

With a user satisfaction score of 90, Oracle is an all-embracing solution that offers a wide range of analytics, reporting capabilities, and intelligence.

User-friendliness – The visualization is incredibly easy for the user to comprehend as it comes in forms of charts, graphs, and other easy to understand graphics. It is even well-suited for non-technical users.

3. Sisense

Sisense is powered by in-chip technology and is a platform that is an analysis, business discovery, and intelligence solution that comes with a back-end powered.

Easy to use – Even non-technical users can easily avail of its merits as it lets them merge and analyze large data sheets from multiple sources.

High compatibility – Its front-end visualization reports are easily understandable and can be viewed on several mobile devices.

4. Microstrategy

The micro strategy is well suited for any small to mid-sized business as it is built for mobile, web, and desktop while it offers a wide range of BI solutions that can be relevant to all levels of users.

User-friendly – Due to the ease of its use, easy comprehension, and high scalability, it is one of the many popular BI tools.

Offers a sea of features – It is equipped with a lot of features like real-time telemetry, social integration, mobile productivity, data discovery, and a lot more.

Looker – Looker, now acquired by Google, is a one-stop solution for all levels of technical users and data analysts.

Highly insightful – This web-based solution lets users explore, visualize, and share actionable data insights.

Customizable dashboards – It lets users customize dashboards for it to reflect in accordance with their particular business needs and Key Performance Indicators.

5. Looker

Looker, now acquired by Google, is a one-stop solution for all levels of technical users and data analysts.

Highly insightful – This web-based solution lets users explore, visualize, and share actionable data insights.

Customizable dashboards – It lets users customize dashboards for it to reflect in accordance with their particular business needs and Key Performance Indicators.

6. Birst

Birst is one platform that functions independent of inputs from the data analyst.

Drives you meaningful insights – It gathers raw data, stores it, puts it into sets, organizes the same, and creates visualizations to discover meaningful insights.

Seamless experience – It highlights imperative patterns conducive to comprehend the enterprise’s KPIs. It lets users perform all the steps of data through a single interface, making the experience seamless with integrated UI.

7. SAP

SAP helps businesses to drive through the decision-making process directionally with a clearer understanding and meaningful patterns derived from the data.

Easy to use – It operates within a familiarized Microsoft Office environment making it easier and more convenient to use.

Create analytical reports – You can create analytical reports with the help of SAP Identity Analytics, while SAP Crystal Server is greatly suited for small businesses to deliver insightful reports, data exploration, and a lot more.

8. Power BI

Power BI is powered by Microsoft and comes with an array of tools to derive the right insights for your organization.

Drive interactive solutions Some of its many capabilities include data discovery, data preparation, along with an interactive dashboard.

Custom visualizations – It doesn’t quite end here as it can load several custom visualizations that work in accordance with the organizational requirements.

9. TeraData

TeraData is one of the leading providers of analytics, Business intelligence, and hybrid cloud products.

Flexible and convenient – It provides very flexible support in terms of working with multiple data, heterogeneous stores, and formats.

High score – According to Gartner, TeraData scores highest for all the use cases.

10. Salesforce Einstein Analytics

In a world fueled by technology, here comes an AI-powered analytics solution by Salesforce, Einstein Analytics. It has especially been developed for the Salesforce customer success platform.

Smart insights – It encompasses all the capabilities of machine learning that help with smart insights and works with automation.

Data forecast – One of its many features is predictive analysis that helps with forecasting data and explanation of imperative insights derived from recorded raw data.

11. SAS

Advanced level analytics – It takes care of several analytic solutions from data management, business intelligence to predictive analysis, and multivariate analysis.

Easy to use – With an impressive user-interface, it makes it easy for even the technical users to have access to its features.

12. Dundas

Powered by Dundas Visualization, Dundas BI is one of the best browser-based business intelligence solutions

Interactive visualization – It comes with a highly interactive dashboard, the ability to build reports, customize visualizations, and a lot more.

High flexibility – It lets users integrate data in real-time from any source providing utter flexibility and high-level convenience.

13. Board

Board is a data discovery platform that is fully featured and helps with enterprise performance management and business analytics.

Interactive experience – It helps its users with a comprehensive overview of their business with its customizable and highly interactive dashboard.

Keeping a check on KPIs – It is conducive for enterprises in drilling down their Key Performance Indicators to keep a regular check on their business performance.

14. DOMO

DOMO translates to ‘thank you’ in the Japanese language. Due to its efficacy in providing its users with the most insightful information to drive the decision-making process, it sure is one of the most popular tools used by analysts.

Comprehensive analysis – DOMO is a SaaS business management platform that gives its users an all-embracing data set for analysis by integrating data from numerous sources.

Need-based solutions – This platform lets users perform both micro and macro levels of analysis depending on the requirement and ultimately generating an in-depth and insightful result for the same.

15. QlikView

Formerly identified as ‘Quality Understanding Interaction, Knowledge,’ Qlik has been inspired by the PC based ‘Quick View.’

Quality experience – It is one of the prominent names when it comes to talking of efficient BI visualization tools providing the best in class quality experience to its user.

High customization – It customizes its products by breaking them down as per the requirements of the user.

16. Google Data Studio

Reporting and data visualization couldn’t have been easier without the existence of Google Data Studio in the analytics space.

Easy to use -Google Data Studio is incredibly easy to use, which makes it possible for analysts at all levels to avail of its impressive features.

Great user experience – It lets you create interesting web reports and is equipped with a smooth user interface for better navigation and convenience.

17. OBI 12C

OBI 12C is a popular business intelligence analytics platform among data analysts.

User-friendliness – Great scalability, powerful decision support system, user-friendliness, easy implementation are just a few of its many key highlights.

Apt for all – It is suitable for all levels of technical and non-technical users due to the ease of its use and implementation.

18. Panorama Necto

Panorama Necto is one of the most efficacious tools that is power-packed with highly useful features that are immensely conducive to drive actionable insights for the user.

Easy comprehension – Panorama Necto is one of the best analytics and business intelligence platforms due to its phenomenal abilities to process data and capabilities to create easily comprehensive yet impressive visualizations.

More for less – Along with its powerful functionality, it also comes at a really affordable price that makes it fit for all sizes of organizations.

19. ZenDesk Explore

Zendesk Explore is a really powerful tool that is highly intuitive to aid organizations with all the data analytics requirements in the smoothest way.

Insightful information – It apt to provide organizations with amazingly useful insights that can drive them through the decision making process.

Easy comprehension – Along with being easy to use, it allows users to analyze data using statistics and visualize the same comprehensively. In addition to this, the User Interface is also really smooth and presentable.

Quintillions of data are produced by businesses every day. The challenge is to record it, maintain it, segregate it, organize it and make sense out of it to derive key actionable insights that can drive organizations through crucial decision-making processes along with optimizing the workflow. Doing all of this manually seems nearly impossible, which is why Business Intelligence analytics tools come into the picture to aid enterprises through the herculean process. Businesses have started to realize its significance and thus are incorporating their use in the system increases.

Data Science Vs Business Intelligence

Introduction

Hadoop, Data Science, Statistics & others

Data Science vs Business Intelligence: Head-to-Head Comparison (Infographics)

Here are the top 20 comparisons between Data Science vs Business Intelligence:

Data Science vs Business Intelligence: Key Differences

Generic steps followed in Business Intelligence are as follows:

Set a business outcome to improve.

Decide which datasets are most relevant.

Clean and prepare the data.

Design KPIs, reports, and dashboards for better visualization.

Set a business outcome to improve or predict.

Gather all possible and relevant datasets.

Choose an appropriate algorithm to prepare a model.

Evaluate the model for accuracy.

Operationalize the model.

Data Science vs Business Intelligence: Comparison Table

Basis Of Comparison Data Science Business Intelligence

Complexity Higher Simpler

Data Distributed and Real-time Siloed and Warehoused

Role Using statistics and mathematics to uncover hidden patterns, analyze data, and forecast future situations. Focused on organizing datasets, extracting useful information, and presenting it in visualizations such as dashboards.

Technology With cut-throat competition in today’s IT market, companies are striving for innovation and easier solutions for complex business problems. Hence, there is a greater focus on data science than business intelligence. BI is about answering complex business questions through dashboards, providing insights that may not be easily discovered through Excel. BI helps to identify relationships between various variables and time periods. It enables executives to make informed business decisions based on accurate data.

BI does not involve prediction.

Usage Data science helps companies to anticipate future situations, enabling them to mitigate risks and increase revenue. BI helps companies perform root cause analysis to understand the reasons behind a failure or to assess their current situation

Focus Data Science focuses on the future. BI focuses on the past and present.

Career Skill

Data science is the combination of three fields: Statistics, Machine Learning, and Programming.

Until now, most reporting tasks and BI tasks have been conducted through Excel.

Evolution Data science has evolved from Business intelligence. BI has been around for a long time, but previously it was mainly limited to Excel. However, now there are a plethora of tools available in the market that offer better capabilities.

Process Data science leans towards novel experimentation and is dynamic and iterative in nature. Business Intelligence is static in nature with little scope for experimentation. Extraction of data, slight munging of data, and finally dashboarding it.

Flexibility Data Science offers greater flexibility as data sources can be added as per future needs. BI has less flexibility. Data sources need to be pre-planned and adding new sources is a slow process

Business Value Data science brings out better business value than BI, as it focuses on the future scope of the business. Business intelligence has a static process of extracting business value by plotting charts and KPIs, thus showing less business value compared to data science.

Thought Process Data science helps generate questions, which encourages a company to run in a strategic and efficient manner. Business intelligence helps answer already existing questions.

Data Quality Data science involves analyzing data using statistical techniques and evaluating the accuracy, precision, recall value, and probabilities. It instills confidence in the decision-makers. BI provides high-quality dashboarding, but only with good quality data. This means that the data should be sufficient to extract insights from the dataset.

Method Analytic & Scientific Only Analytic

Questions What will happen?

What if?

What happened?

What is happening?

Approach Proactive Reactive

Expertise Role Data scientist Business user

Data Size The tools and technologies are not enough to handle big datasets.

Use cases Not a periodic task. Many of the use cases of BI involve generating and refreshing the standardized dashboards.

Consumption Data science insights are consumed at various levels, from the enterprise level down to the executive level. Business intelligence insights are consumed at the enterprise or department level.

Conclusion

Business intelligence is undoubtedly a beneficial starting point for any industry. However, in the long run, adding a layer of data science will ultimately set it apart. The ability to predict the future by analyzing data is an achievement of data science. Therefore, data science plays a pivotal role and is superior to business intelligence.

Recommended Articles

Here are some further related articles to the subject:

Business Intelligence In Manufacturing Industry

Why Is There A Compelling Need for BI in Manufacturing?

Manufacturing costs are increasing rapidly coupled with declining profit margins. Increased regulations from governments are also making the path harder to traverse. In this backdrop, the demand for simple, data-driven insights is greater than ever. Moreover, manufacturing is one of the most data-intensive industries.  From reaching out to customers to delivering products, by nature, manufacturing is an extensively data-intensive industry. However, most of these data often lie idle with the companies. So,

Informed Decision-Making

With the huge influx of data from multiple sources, there arises a need for proper management, storage, and utilization of all these data. BI can help in management and utilization of data from multiple sources. BI tools can access large, cumbersome database and transform it into an easily comprehensible structure. With the help of visualization tools, the analysis can be presented in a simplified manner along with key business matrices and KPIs to business executives. This helps the decision-makers to take a more informed and concise decision. Information from all sources can be sophistically incorporated in the decision making. It can also test ‘what if’ scenarios to project and analyze alternate strategies. This, in turn, increases the risk-taking capability of a business.  

Increases Operational Efficiency

BI accelerates the pace of operational efficiency by making huge volumes of data readily accessible and understandable. It can help in analyzing team performances and suggesting remedial measures for proper allocation of scarce resources. Product modeling through analytics helps to reduce and correct errors during product development. By incorporating viable financial models, BI can evaluate capacity and material requirement periodically. Almost every complex process from production to shipping can be simplified by using BI. From constantly changing market demands to sales strategy, forecasting and supply chain management, BI can take care of all. It also helps to bring more transparency to the network.  

Financial Management

BI tools can be used for profit and loss analysis, sales analysis, raw material analysis, and thus help in optimizing resources and increase ROI. Both external profit building and internal cost reductions are necessary to improve the profit margin. BI can help in this case by identifying new unexplored channels of revenue and minimizing internal costs. It allows to do an in-depth cost-benefit analysis that helps companies to manage production costs through multiple information layers. It also helps to streamline operational procedures by managing and monitoring processes. With demand-supply analysis, BI can control value chain more efficiently.  

Supply Chain and Logistics Management

BI can help in managing the supply chain logistics by evaluating its performance on a daily basis and analyzing data to ensure timely deliveries and quality service. It can monitor freight costs by identifying changes in supply and demand. It can also help to optimize the value of suppliers by giving feedback on their services. Thus, BI can help to evaluate shipment performances and accordingly negotiate contracts.  

Inventory Control

Inventory control and management is one of the most crucial operations of a manufacturing firm. It is one of the biggest assets of any firm and can regulate the performance of the firms accordingly. It can also help in tracking and reducing inventory costs across location and time. Testing and simulating new manufacturing products also becomes easier. This helps in reduced process flaws by pin-pointing defects. It can also analyze turnover rates and margins based on products, departments and sellers.  

Conclusion

Plan Your Business Startup With Startup Product Manager For Windows

Planning to get your business up and running? What if you could predict where your production business would end up in a few years from now, wouldn’t that be swell? This is not easy unless you have a fortune teller or just some guy who is capable of traveling to the future and back. The Flash, maybe?

Thanks to a  software known as Startup Product Manager earlier called Predicted Desire, you won’t have to rely on a fortune teller or some comic book character, because it can all be done with this simple program. Bear in mind, this is just a software designed by human developers, don’t go in expecting magical things to happen out of thin air.

NOTE: Predicted Desire is now called Startup Product Manager (StPM).

Startup Product Manager for Windows

Startup Product Manager is a free Windows software forecasts & tells you how much money you need to start and run a business. It is a startup product calculator.

From what we can tell, the software is capable of calculating different things that have to do with a business. For example, cost, net profit, and efficiency, are just some of the things this program can deal with. Right away you can see the combined effects for up to 48 months, so from there, business owners can plan out their future.

After launching Startup Product Manager for the first time, the program shows us a calculator and a window that required us to choose our specified simulation. After that, the software will eventually display the main window to get things up and running to what users want to see.

The following are some input parameters that we could specify:

Number of employees

Salary per hour

Work hours per day

Work days per month

Fixed cost per month

Fixed income per month

Energy cost

Price

Daily sales

Daily production

When it comes down to target values, the following is what the program allowed us to choose from:

Bank account balance

Total income per month

Net profit per month

Total cost per month

Total production cost per month

Total material and energy cost per month

Daily employee production time

Total employee cost per month

Single employee cost per month

Daily income

Daily production cost

Single unit/product production

At the top of the main user interface, there’s a slider that allows us to choose our desired period. It can be anywhere between January 2024 and January 2023. At the lower section, it displays the date and a total number of months.

Startup Product Manager will draw up graphs in real-time, and it all depends on the choices made. There’s also something called the Result Graph, and this displays the development of all specified input and target values covering the selected time-frame.

Bear in mind that some curves have similar colors, so if you want to focus on a single one, chances are, you might have to disable a few and only leave the main curve in focus.

Verdict

Startup Product Manager is a great financial tool, just don’t go in expecting it to be easy to understand. It’s difficult at times, but once you get it and know what you want the program to do for you, then it should be smooth sailing after a time.

Download Startup Product Manager from the official website.

Best Linux Video Editing Software To Get This Year!

Best Linux Video Editing Software To Get This Year!

Moving ahead, if you are already using this OS and looking for a video editor on Linux, you are at the right place! We have created a list of

Best Linux video editing software 2023 1. Kdenlive- Video Editor Linux

Kdenlive is considered as the best Linux video editing software. This is freebie software that comes up with a bunch of amazing features that includes unlimited video and audio tracks along with adjustable effects and transitions. 

Kdenlive offers support for PAL, 4:3 NTSC, 16:9, and HD standards. Other highlights include masking, blue-screen, keyboard shortcuts, multi-track timeline editing and a lot more. Oh! I forgot to tell you, this is a free video editor for Linux OS. Kdenlive is built on QT and KDE Frameworks libraries and its video processing is operated by the MLT framework. 

This is one of the renowned Linux video editing software. You can download Kdenlive from here

2. OpenShot- Best Linux Video Editing Software

OpenShot is our next pick in this list. It has an amazing streamline feature and smart transitions with 2.5 versions. When we talk about its features, OpenShot is capable of dealing with video and audio formats without any effort. Another highlight feature of this Linux video editing software is that Windows and mac OS can also install this on their system.

This is a user-friendly video editor for Linux and offers various titles, transitions, and support in professional video formats, exporting of various files, visualizing waveform, splitting the audio from video clips and dealing with every audio channel in an individual manner. 

You can get this amazing and free video editor for Linux from here

3. Shotcut

Shotcut is especially for novice users and considered as open-source, free and cross platform Linux video editing software. This amazing software inherits a broad range of features such as video transitions, filters, multi-track timeline, native timeline editing and much more. 

Shotcut can also enable quick edit in 4K audio and video, hence also supports external monitoring. When it comes to adjusting audio fronts, Shotcut offers support in JACK transport syncing, audio mixing in mono, stereo, track formats. 

Sounds interesting? Get this smart and free video editor for Linux from here.

Also Read: How To Install ADB On Windows, Mac, Linux, And Chrome OS

4. Flowblade

Well, we always come across with a situation when trying with new software, we often face lagging issues. So, if you have already used the above mentioned video editors for Linux and looking for smart software that doesn’t lag, Flowblade could be your take.

Flowblade operates in Python that makes it run smoother and faster than any other competitors. This video editing software offers a user-friendly interface with a wide range of amazing features. Users will adore its video transitions, drag & drop support, watermarks, support in various audio, image, and video formats. In addition to this, Flowblade also inherits batch rendering, proxy video editing.

This Linux video editing software is available on all major browsers.

5. Lightworks

Here comes the Lightworks, the last pick on our list of the best Linux video editing software. We have listed the novice software on our list but Lightworks is suitable for professional users. This NLE video editor offers support in 4K, SD, HD formats, Low-Res Proxy workflow and Blu-Ray, alongside drag & drop support. 

In addition to its features users will adore analog & digital connections that comprises AES, EBU connectors, 3G-SDI, Optical audio, HDMI 2, 12 G and other high-quality audio and video filters effects. This is not a free video editor for Linux. You can use Lightworks on Windows and macOS too. 

This best Linux video editing software is available on all major browsers. 

Final Words

That’s all folks!  We have shared a list of best Linux video editing software for you. Share your views and feedback related to this topic. I hope you like this article and have subscribed to our newsletter for amazing tips and tricks.

Don’t forget to tell us which of the best video editors you have chosen for Linux OS. Yes! We are open for conversation too! 

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