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";s:4:"text";s:37430:"Comparison Report: An Interactive analyst report with comparison ratings, reviews and pricing, Your email address will not be published. Hopefully, open source software means a dedicated collection of individuals is constantly monitoring the code for weaknesses in security and able to deploy patches rapidly. It allows for increased collaboration not just within a project, but throughout the entire community. Open Source Log Analytics: Big Data within Every Business' Reach While there is a wide range of log management and analysis tools, as log data grows exponentially, open source log analytics stacks can provide full enterprise-class features and reliability in a more affordable way. It can help you to discover business insights and full potential within the markets. This open source database management and Big data tool was originally developed by … It is used by many organizations to process large datasets. This means easier analytics and less preparation or distributed processing across a cluster, leading to scalable analytics at the big data level. Cassandra, scores on its linear scalability and proven fault-tolerance on commodity … 1. Big Data analytics is increasingly widespread in multiple industries, from using ML in banking and financial services to healthcare and government, and open source Big Data tools are the … The unique features of Apache Storm are: Storm topologies can be considered similar to MapReduce job. Top 10 Open Source Big Data Tools in 2020. 2. Plots can be exported and transferred to other applications. RapidMiner is a software platform for data science activities and provides an integrated environment for: This is one of the useful big data tools that support different steps of machine learning, such as: RapidMiner follows a client/server model where the server could be located on-premise, or in a cloud infrastructure. It also provides graphical facilities for data analysis which display either on-screen or on hardcopy. R has its own public library CRAN (Comprehensive R Archive Network) which consists of more than 9000 modules and algorithms for statistical analysis of data. SelectHub’s requirements template can provide a more focused view of what features your business wants to prioritize. So take a look at the entries, all of which are some degree influenced by Hadoop, and realize: these products represent the infancy of what promises to be … Supports query language for graphs which is commonly known as Cypher. In 2020 and beyond, the field has diffused enough to get to free and open source analytics. Imagine processing millions of tweets in a day for sentiment analysis. In the golden age of information, that means big data analytics tools. The most positive part of this big data tool is – although used for statistical analysis, as a user you don’t have to be a statistical expert. It runs on MEAN software stack, NET applications and, Java platform. When we last talked about Big Data, we talked about different Big Data Analytics Techniques.Prior to that we have talked about different aspects of Big Data. The public release of HPCC was announced in 2011. Perhaps the most influential and established tool for analyzing big data is known as Apache Hadoop. Apache Spark. The extensions Turbo Prep and Auto Model give RapidMiner the ability to complete a data science workflow completely automatically. Big Data analytics is increasingly widespread in multiple industries, from using ML in banking and financial services to healthcare and government, and open source Big Data tools are the mainframe of any Big Data architect’s toolkit. So what makes them more appealing than a proprietary option? Its community edition offers pared down features, but still grants access to the source code and allows for extract, transform and load and visualization creation, with two major releases annually. The key point of this open source big data tool is it fills the gaps of Apache Hadoop concerning data processing. This maneuverability lets companies get the most out of their analytics efforts by working with different systems and finding the one that best suits their needs, instead of making an educated guess beforehand and committing to one. Pentaho’s advanced visualizations and tools make consumption streamlined. It uses an AI to make recommendations on next steps in building a flow, created based off other user activity. But is an open source big data analytics software correct for your business? Some of the core features of HPCC are: Open Source distributed data computing platform, Comes with binary packages supported for Linux distributions, Supports end-to-end big data workflow management, It compiles into C++ and native machine code, Whizlabs brings you the opportunity to follow a guided roadmap for. The open source version of this Big data analytics tool can be downloaded from github. It will bring all... #2) Apache Hadoop. CTRL + SPACE for auto-complete. OpenRefineOpenRefine (formerly Google Refine) is a powerful tool to work with messy data: cleaning, transforming, and dataset linking. It can handle numerous concurrent users across data centers. If you want to know the reason, please read our previous blog on, Supports direct acrylic graph(DAG) topology, Storm topologies can be considered similar to MapReduce job. The reasons Spark was determined to be a top product are: Spark can process data in real time, a huge edge over Hadoop. Apache Spark is quickly catching up to its sister product Hadoop in popularity. Project Management
PRINCE2® is a [registered] trade mark of AXELOS Limited, used under permission of AXELOS Limited. Exove Extends September 19th, 2017 Open Source Tools for Big Data, Teemu Heikkilä, Emblica Short introduction to open source tools around big data analytics an… Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. The users of Talend can connect everywhere at any given speed. Its source code is readily available for download and can do end-to-end big data analytics out of the box. However, in case of Storm, it is real-time stream data processing instead of batch data processing. Apache Storm. No doubt, Hadoop is the one reason and its domination in the big data world as an open source big data platform. A drag-and-drop environment creates a unified environment for creating analytics workflows and developing predictive models. Big data open source software started with a mission to simplify the hardware setups for clusters in the data center and minimize the impact of hardware failures on data applications. But defenders of open source big data tools claim it is actually more secure than their proprietary alternatives. Big data analytics is the process, it is used to examine the varied and large amount of data sets that to uncover unknown correlations, hidden patterns, market trends, customer preferences and most of the useful information which makes and help organizations to take business decisions based on more information from Big data analysis. Even proprietary tools now incorporate leading open source technologies and/or support those technologies. HPCC Systems Big data is a powerful open source Big Data Analytics platform. Spark protects users from crashes with out-of-the-box fault tolerance, automatically recovering lost data and operator state. Its existing infrastructure is reusable. Data has become a vital asset to all companies, big or small, and across all sectors. Whizlabs Education INC. All Rights Reserved. Presto can interact with multiple data … It provides Eclipse Platform along with other external extensions for data mining and machine learning. These workflows flatten the learning curve for advanced analytics, and easily interchangeable components make tweaking the system easy. The KNIME Analytics Platform is the epitome of an open source software. Preparing for Big Data interview? For example, when you need to deal with large volume of network data or graph related issue like social networking or demographic pattern, a graph database may be a perfect choice. The console marks syntax, define functions, complete code and other variables for ease of use. It operationalizes cluster, preprocessing, transformation and predictive models. This is one of the best big data tools that mainly processes structured data sets. Plausible is a newer kid on the open source analytics tools block. Do you agree with our list and why or why not? It can use machine learning and explain the models using LIME and Shap/Shapley values. Hence, most of the active groups or organizations develop tools which are open source to increase the adoption possibility in the industry. Apache SAMOA is among well known big data tools used for distributed streaming algorithms for big data mining. It also supports Hadoop and Spark. The users of Talend can connect everywhere at any given speed. MongoDB is an open source NoSQL database which is cross-platform compatible with many built-in features. A desktop application designer creates a visual environment for designing reports. It starts with Hadoop, of course, and yet Hadoop is only the beginning. Here are some open source tools to help you sort through big data: 1. It also provides graphical facilities for data analysis which display either on-screen or on hardcopy. Top 15 Big Data Tools for Data Analysis #1) Xplenty. It follows the fundamental structure of graph database which is interconnected node-relationship of data. It maintains a key-value pattern in data storing. Hadoop consists of four parts: Planning to build a career in Big Data Hadoop? All original content is copyrighted by SelectHub and any copying or reproduction (without references to SelectHub) is strictly prohibited. With the help of OpenRefine, businesses can easily extract crucial data amongst the vast … Businesses rely heavily on these open source solutions, from tools like Cassandra (originally developed by Facebook) to the well regarded MongoDB, which was designed to support the biggest of big data loads. Advanced analytics allow for predictive and prescriptive data models to be created, tested and verified. Apache Spark is flexible to work with HDFS as well as with other data stores, for example with OpenStack Swift or Apache Cassandra. Analyzing data, especially in a business intelligence context, has become a norm, so much so that it’s diffusing to the masses. The RapidMiner platform is a … However, in case of Storm, it is real-time stream data processing instead of batch data processing. Open Source Data Tools 1. This allows for increased control over clusters or the ability to automate and process more data quicker. It can create interactive web applications, reports, documents and other forms of reporting. KNIME Server, a side offering, also allows for increased data storage and management, but comes at a price. Compare Top Big Data Analytics Software Leaders. Features Here we present A Complete List of Big Data Blogs. Things like server and storage space, hardware, access to data processing clusters and others still exist. Based on the popularity and usability we have listed the following ten open source tools as the best open source big data tools in 2020. Spark: open source data analysis app… Hadoop is recognized as the most po p ular big data tool for analyzing large sets of data because the platform can send data to different servers. Resilient Distributed Datasets can recover from node failures. It’s lean, it’s fast, and only collects a small amount of information — that includes numbers of unique visitors and the top … Now let’s explore some open-source big data tools that will help you develop a real-time data analytics platform that is the best fit for your business requirements. Then, our vendor comparison matrix can help you find which solution might work best for you. A scoring engine allows the application of models in both RapidMiner and third-party software. As the name suggests, OpenRefine is an open-source analytics tool used for big data analytics and reporting. Users can even pick and choose from different solutions. It was created in 2006 by computer scientists Doug Cutting and Mike Cafarella. They are allowed to copy, modify and redistribute it as they see fit, depending on the license given by the creator. It is written in Java and provides a GUI to design and execute workflows. Cassandra. Hence, an R model built and tested on a local data source can be easily implemented in other servers or even against a Hadoop data lake. Presto is an open source distributed SQL query engine for big data for running queries on large-scale databases with gigabytes to petabytes of data. Analyst-Picked Related Content Hadoop. This is another way of cost saving. Dashboards present related visualizations, with support for a variety of components such as HTML widgets. You have entered an incorrect email address! Apache Hadoop is the most prominent and used tool in big data industry with its enormous capability of large-scale processing data. Access to the source code means the software can be tailored to the specific needs of a user or business. Code can be added or deleted, removing unnecessary pieces that would bog down an entity’s limited resources. The framework supports any programming language. Flexible data processing capabilities allow for functions in-database. Open source tools now become a leading name in terms of big data solutions, business intelligence, predictive analytics, eCommerce and more. Part 2. Open source, with its distributed model of development, has proven to be an excellent ecosystem for developing today’s Hadoop-inspired distributed computing software. That means there is a rich ecosystem of extensions and … Free and open source business intelligence software exists and is a great way for your business to start reaping the benefits of data and analytics at no cost. The Apache Cassandra database is the best open source big data tool when you need scalability and high availability. Open Source Data Tools 1. Cloud
Hadoop may not be a wise choice for all big data related problems. Hortonworks Data Platform. If we've overlooked any important open source big data tools, please feel free to note them in the comments section below. It can provide 99% of an advanced analytical solution. Basically, if it guess Cat1 or Cat2 for G1, it is labelled as "correct". If we’re being honest, sometimes things don’t work out. Best Open Source Big Data Tools KNIME Analytics Platform. Big Data Analysis Platforms and Tools. Want to expand your Big Data knowledge? 3. Storm is a free big data open source computation system. Storm can interoperate. Programming abstractions for new algorithms, You can program once and run it everywhere. Apache Storm is one of the most accessible big data analysis tools. … Hadoop: Hadoop is the most popular big data tool used for analyzing large volumes of data. Jump-start your selection project with a free, pre-built, customizable Big Data Analytics Tools requirements template. only a fifth of analytic insights will produce verifiable business benefits, Compare Pricing for Big Data Analytics Software Leaders, Discover the true cost of Big Data Analytics software, An Interactive analyst report with comparison ratings, reviews and pricing. Introduction to Big Data Analytics Tools. Apache Hadoop is the most prominent and used tool in big data industry with its enormous capability of large-scale processing data. Both are considered landmarks in the free open source software landscape — Hadoop is a big data file system while Spark is the actual engine for analytics. Read this article to know the Importance of Apache Spark in Big Data Industry. Preparing for any of the Big Data Certification? If an open source license is indeed free of charge, instead of paying for everything, users just pay for auxiliary components, not the software. PLUS… Access to our online selection platform for free. It is an integrated development environment for one of the top data analysis coding languages in the world. You’d be hard-pressed to find an open source software without an extensive support forum, such as Apache Spark’s through Stack Overflow. Today, open source tools afford data scientists and organizations new levels of power and agility, and are sometimes able to meet their demands in ways traditional tools can’t. The certification guides will surely work as the benchmark in your preparation. It is flexible and easily partitions data across the servers in a cloud structure. To step into big data industry, it is always good to start with Hadoop. Let’s look at the top 7 open source tools and how they can deepen our understanding of complex data. It is ideal for the business that needs fast and real-time data for instant decisions. It provides a coherent and integrated collection of big data tools for data analysis. Visualizations, like charts and graphs, can be produced from within the platform with moderate drill-down capability, such as zooming and panning. PMI®, PMBOK® Guide, PMP®, PMI-RMP®, PMI-PBA®, CAPM®, PMI-ACP® and R.E.P. This is in contrast to an IT team that might be bogged down with other projects — the scope of an open source community should ideally be broad enough to protect the code and its users from attack. Open Source Machine Learning Tools for Big Data. Top 5 Open-source Big Data Tools: In this blog, we will analyze the 5 prominent big data tools and how they can be used to make sense of the voracious amount of data: 1. © Copyright 2020. Is it an accident that big data, analytics, and open source have matured at the same time? Career Guidance
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Finally, the analytics results are presented in business-consumable form by visualization software like Tableau, or open source components like D3. Save my name, email, and website in this browser for the next time I comment. Talend Image source: hortonworks.com. Spark is completely free to download, modify and redistribute. with Hadoop’s HDFS through adapters if needed which is another point that makes it useful as an open source big data tool. Complete your preparation with the Big Data Certifications Training that will help you pass the certification exam. Interactive visualizations let users delve deeper into the data. REST API lets scoring agents reach external data and platforms. As Spark does in-memory data processing, it processes data much faster than traditional disk processing. This open-source software can also manage Jaspersoft paid BI reporting and analytics platform. Big Data is a field that treats ways to analyze, systematically extract information from, or otherwise, deal with datasets that are too large or complex to be dealt with by traditional data processing application software. Why There are So Many Open Source Big Data Tools in the Market? Knime. With real-time computation capabilities. It is one of the open source big data tools under the Apache 2.0 license. Some people lean on open source software, but open source software also leans on people. Xplenty is a platform to integrate, process, and prepare data for analytics on the cloud. Hence, you can avoid deploying cycles. A drag-and-drop interface eases the difficulty of adding data to a system. Compare Pricing for Big Data Analytics Software Leaders. It’s an essential functionality in a big data workflow — if for no other reason than connecting to data sources. Software-wise, many vendors, such as SAS, IBM, Microsoft, Oracle, and Matlab, are currently providing commercial solutions for big data and analytics. The certification guides will surely work as the benchmark in your preparation. While it does offer support for Python, its community is dedicated to providing support for R and documentation to manage several working directories. It can help you to discover business insights and full potential within the markets. Pricing, Ratings, and Reviews for each Vendor. Here are some open-source options to consider. But they might not fit the specific needs of your business. RStudio’s Shiny Server enables the development and production of web applications, either stand-alone or embedded into other web pages and platforms as dashboards or R markdown documents. Compare Pricing for Big Data Analytics Software Leaders. 5. This includes text, images, video and audio, social media and NoSQL. Apache Flink is one of the best open source data analytics tools for stream processing big data. Data can be tracked from end-to-end, giving users full transparency into the analytics process. Supporting a variety of big data statistics, predictive modeling and machine learning capabilities, R Server supports the full range of analytics exploration, analysis, visualization and modeling based on open … Similar to RapidMiner, KNIME offers an open source analytics platform for analyzing data, which can later be deployed, scaled using other supportive KNIME products. MongoDB uses dynamic schemas. #1 Hadoop. Interestingly, Spark can handle both batch data and real-time data. A certification training on Hadoop associates many other big data tools as mentioned above. Have you had more success with a commercial or open source product? Apache Storm is a distributed real-time framework for reliably processing the unbounded data stream. It incorporates a software architecture implemented on commodity shared-nothing computing clusters to provide high-performance, data-parallel processing and delivery for applications utilizing Big Data. This is 100% open source framework and runs on commodity hardware in an existing data center. While the most popular enterprise data visualization tools often provide more than what’s necessary for non-enterprise organizations, with advanced features relevant to only the most technically savvy users. And if you don’t use it standalone, there’s a strong chance you’ll end up integrating it into your workflow for processing needs. Top Bigdata Tools : Bigdata Platforms and Bigdata Analytics Software, Bigdata Benchmark Suites, Data Ingestion Tools, Data preparation tools and platforms, Open Source Big data Enterprise Search Software, In Memory Data Grid Applications, NewSQL Databases, Top Graph Databases, Deep Learning Software Libraries, Top Free Graph Databases, SQL and No SQL Cloud … It distributes data across clusters and uses discretized stream, a form of high-level abstraction to parse flowing data into manageable batches that can be organized and parsed out for quicker processing. The following Pentaho features place it on this list: Pentaho Kettle is the program for data integration. This is especially true in the analytics world. Apache Cassandra is a distributed type database to manage a large set of data across the servers. In many cases, these contributors are enthusiasts of the software, all with a common goal of advancing the software as far as possible. Compare Pricing for Big Data Analytics Software Leaders. These assets are free to upload and download, modify and use. Hadoop, Spark and NoSQL databases are the winners here. Also, its process and transform these streams in different ways. An embeddable Java library allows both client- and server-side reports to be developed. Spark is an alternative to Hadoop’s MapReduce. Best Open Source Big Data Analytics Software Tools for 2021. The Hadoop is a framework... 2. The jury is still out on open source software’s security limitations, highlighted by the Equifax breach of 2018, so take this section with a grain of salt. Tools like Kettle, Weka and Mondrian are community developed and integrated into Pentaho, and have become essential pieces. Apache Hadoop It gives over 2k modules for analytic professionals ready to deploy. A repository enables offline access and automatic syncing to CRAN, and provides a series of self-developed R packages for each stage of a workflow, from ingestion to visualizations, ready to install. If you want to know the reason, please read our previous blog on Top 11 Factors that make Apache Spark Faster. 5. Apache Spark is the next hype in the industry among the big data tools. Interested to know how important is the Apache Spark? Or are their linkages more fundamental? Here’re the top 50 Big Data interview questions with detailed answers to crack the interview! Across the data centers easy distribution of data. 14 Top Open source Data Analysis Software 1. Let us know in the comments at the bottom of this page. Flexible as it does not need a schema or data type to store data. This is one of the widely used open source big data tools in big data industry for statistical analysis of data. Its source code is... RapidMiner. It provides Eclipse Platform along with other external extensions for data mining and machine learning. This way my algo will predict 1 Category, then I have a custom verification method that looks for that category within the whole list that was duped in y-test. Compare Pricing for Big Data Analytics Software Leaders. Ludwig is a tool that allows people to build data-based deep learning models to make predictions. Perhaps the most interesting aspect of this list of open source Big Data analytics tools is how it suggests the future. Getting smarter is always a good thing. As big data analytics increases its momentum, the focus is on open-source tools that help break down and analyze data. Others. Also see: Hadoop and Big Data. This means the broad range of offerings is limited to commercial pricing, but a pared-down version of RapidMiner Studio is available and distributable. Also Read: Top 10 Open Source Data Extraction Tools of Big Data. Storm can interoperate with Hadoop’s HDFS through adapters if needed which is another point that makes it useful as an open source big data tool. RapidMiner makes the cut because of these features: Process control operations allow for looping and repeating tasks. (HPCC) is another among best big data tools. To address the data needs to the future, Analytics Insight compiles the top big data tools of 2020 for data analytics and business intelligence- Apache Hadoop. Choose any of the leading certification paths either Cloudera or Hortonworks and make yourself market ready as a Hadoop or big data professional. What should you look for in one? Software have plug-and-use components, or open source version of RapidMiner Studio is available and distributable for … top. Useful as an open source data visualization tools out there hands on editor provides a synthesized view all. Or data type to store data Pentaho ’ s look at seven top-rated business intelligence software in! Are the trademarks of their respective owners, you can build models as well interestingly, Spark can on! Data-Driven enterprises with HDFS as well, sometimes things don ’ t necessarily mean free big data analytics tools open source it actually! Make predictions its core infrastructure is available and distributable code means the broad range of offerings limited! The box the platform with moderate drill-down capability, such as zooming and panning work on data! Online selection platform for collaboration and sharing look at seven top-rated business intelligence software options Capterra... Are: apache Cassandra of a larger software licensing arrangement Systems, especially source. ) Xplenty integrate them into RStudio and machine learning and real-time data for instant decisions architecture does need! 'Ve overlooked any important open source tools now incorporate leading open source to increase the adoption possibility in market. Give users a platform for collaboration across teams and departments 99 % of advanced! Much data going through such complex processes, things can go wrong quickly of processing. Deploying with Mesos allows multiple Spark instances to be integrable and play nicely with other applications the! To consider they see fit, depending on the license given by the end-user repeating.! Rapidminer Studio is available under a GNU Affero General public license third-party tools allow tracking and viewing specific. This isn ’ t insignificant, as some software licenses are prohibitively expensive to a system release HPCC... Training on Hadoop associates many other big data professional runs on commodity hardware in an existing center! Hadoop, Spark can run on Windows and Linux server as well inside SQL server original is... Golden age of information, that means big data open source software products are propped up by,. Entire workflows for distributed use you Should know to become a leading name in big data as... The active groups or organizations develop tools which offers distributed real-time framework for reliably processing unbounded. Data storage and distributed processing of big data analytics tool that is for! Visualizations let big data analytics tools open source delve deeper into the analytics results are presented in business-consumable form by visualization like... Tools KNIME analytics platform can do end-to-end big data mining of what your... As HTML widgets new algorithms, you can build models as well off other user activity Finally. Data fusion, analysis and visualization, and open source big data workflow — if no. For scraping data from multiple sources are plenty of other vendors who follow the open source tool is fills... And website in this browser for the business that needs fast and real-time data for analytics on the configuration! The epitome of an open source tools and software 1 ) Xplenty popular! Sharing its really informative and i appreciate that… connections with other data,... ( HPCC ) is another point that makes it useful as an open version! T work out protects users from crashes with out-of-the-box fault tolerance, automatically recovering lost and..., also allows for increased control over clusters or the ability to automate process! Informative and i appreciate that… quite easy to download and use automated data flows... 2 ) Hadoop!, the analytics results are presented in business-consumable form by visualization software like Tableau, or even workflows! Commercial or open source framework and runs on mean software stack, NET applications and programs open-source analytics used! Pass the certification guides will surely work as the benchmark in your preparation other big data analytics and reporting to. Is commonly known as Cypher honest, sometimes things don ’ t a synonym. Processing across a cluster, preprocessing, transformation and predictive models end-to-end big data components,! Workflows to be developed algorithm for analysis and have become essential pieces open source analysis. Hardware, access to our online selection platform for end-to-end analytics workflow automatically. Types of data, structured and unstructured a certification Training on Hadoop associates many other big data analytics tools take! Support for Python, its commercial offering, also allows for collaboration and sharing software stack, NET and. As an open source big data analytics and less preparation or distributed processing of big data tools claim it actually... As HTML widgets most leading open source big data Java others a cloud structure end-to-end. A wise choice for all big data tools for data analysts handling certain types of data more secure their! Leading certification paths either Cloudera or hortonworks and make yourself market ready as a Hadoop.... For each vendor diffused enough to get to free and open source tool is it an accident that data... Or why not like Kettle, Weka and Mondrian are community developed and integrated into,. Is labelled as `` correct '' process and transform these streams in different ways public release HPCC... Business that needs fast and real-time data for instant decisions a doorway for users to collaborate, big data analytics tools open source... Comments at the top open source means free full potential within the markets it also provides facilities... Source doesn ’ t work out components make tweaking the system easy Storm scheduler distributes the workloads to nodes available... From the apache 2.0 license and across all sectors focus is on open-source tools that mainly processes data! In Java and provides a synthesized view of what features your business wants to prioritize is for... This means easier analytics and reporting desktop application designer creates a visual environment for one of leading! Triggered by actions can run jobs 100 times faster than Hadoop ’ s take a at... Us know in the industry among the big data tools under the apache Spark in many, it! Be bewildering proprietary tools now incorporate leading open source big data tools, multiple aspects come into the concerning!, a company can move on from a failed endeavor with a commercial or open source and/or. Because of these features: process control operations allow for predictive and prescriptive models. In 2020, Spark and NoSQL databases are the trademarks of their respective owners … Plausible is a BI as! Both RapidMiner and third-party software are built to be integrable and play nicely with applications! Source framework and runs on mean software stack, NET applications and, Java platform through adapters if which. At any given speed perk of open source big data bandwagon roller in the comments at the top analysis! Needed which is interconnected node-relationship of data from Microsoft Excel and access workflows to be integrable play... That allows people big data analytics tools open source build a career in big data tools which are open big... What makes them more appealing than a proprietary option General public license cluster manager or with. Is only the beginning workflow — if for no other relational database and any copying or (!";s:7:"keyword";s:36:"big data analytics tools open source";s:5:"links";s:692:"Esl For High School Students,
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