Platfora vs Tableau
Last updated: June 10, 2019
Platfora's Big Data Discovery and Analytics platform is the only end-to-end solution native on Hadoop + Spark. Know everything your big data is telling you with the platform that gives you everything. Platfora brings together traditionally separate tools—data prep, in-memory acceleration, BI, analytics, and visualization—to streamline big data analytics and simplify data discovery.
Tableau complements your natural ability to understand data visually. Our breakthrough products let you create rich analyses and share your insights with colleagues in seconds. Connect and visualize your data in minutes. Tableau is 10 to 100x faster than existing solutions. From spreadsheets to databases to Hadoop to cloud services, explore any data with Tableau.
Platfora vs Tableau in our news:
2019 - Salesforce acquires data visualization company Tableau for $15.7B
Salesforce is buying Tableau for $15.7 billion in an all-stock deal. This is a huge deal for Salesforce as it continues to diversify beyond CRM software and into deeper layers of analytics. The company reportedly worked hard to — but ultimately missed out on — buying LinkedIn (which Microsoft picked up instead), and while there isn’t a whole lot in common between LinkedIn and Tableau, this deal will also help Salesforce extend its engagement (and data intelligence) for the customers that Salesforce already has — something that LinkedIn would have also helped it to do. This also looks like a move designed to help bulk up against Google’s move to buy Looker, announced last week.
2018 - Tableau acquired AI-analytics startup Empirical Systems
Enterprise BI giant Tableau has acquired Empirical Systems, an early stage startup with AI roots. Their product is still in private Beta. It is delivered currently as an engine embedded inside other applications. That sounds like something that could slip in nicely into the Tableau analytics platform. What’s more, it will be bringing the engineering team on board for some AI knowledge, while taking advantage of this underlying advanced technology. Empirical was developed to make complex data modeling and sophisticated statistical analysis more accessible, so anyone trying to understand their data can make thoughtful, data-driven decisions based on sound analysis, regardless of their technical expertise. So we may assume that Tableau gets better AI-expertise in comparison to Adaptive Insights
2018 - Tableau gets a new data preparation tool
Data analytics platform Tableau launched a new data preparation tool. The general idea here is to give users a visual way to shape and clean their data, something that’s especially important as businesses now often pull in data from a variety of sources. Tableau Prep can automate some of this, but the most important aspect of the service is that it gives users a visual interface for creating these kind of workflows. Prep includes support for all the standard Tableau data connectors and lets users perform calculations, too. Also the company added server plan for businesses that want to deploy the service on-premises or on a cloud platform, and a fully hosted online plan. Prices for these range from $35 to $70 per user and month. Thereby Tableau gets better data preparation feature than Adaptive Insights
2017 - Tableau reveals Linux version to win over Zoomdata
Business Intelligence software provider Tableau announced Tableau Server on Linux, which gives a new option to users who do not want to run it on Windows Server. Besides, Tableau acquired HyPer, a startup that created Hyper, a main memory database for precisely that reason. It brings performance, faster loading and scalability according to Ajenstat. It replaces Tableau's TDE database, and is part of Tableau 10.5 which is available now in beta. Also Tableau has opened its API, inviting users to integrate and work with third-party applications directly in Tableau. Thus Tableau becomes more Linux-friendly than Zoomdata
2017 - Tableau acquired natural language processing startup ClearGraph to catch up with Datazen
Business intelligence solution provider Tableau has acquired ClearGraph, a service that lets you query and visualize large amounts of business date through natural language queries. Tableau expects to integrate this technology with its own products as it looks to make it easier for its users to use similar queries to visualize their data. Recent advances in natural language processing and machine learning now allow ClearGraph and Datazen to understand more about the underlying database and then take these sentences and essentially translate them into database queries. Given that Microsoft’s Power BI and other competitors already offer this capability, it’s no surprise that Tableau is also looking into this.
2016 - Tableau to launch visual data-prep software with deep learning to catch up with Watson Analytics
Tableau is moving into the data-wrangling business, announcing plans for visual data-preparation software code-named Project Maestro. The idea is to bring the same sort of "self-service" visualization to the prepping and cleaning of data as they've built for data analysis. Besides the company is going to implement Natural Language Processing (NLP) to bring new ways to interact with data through human language such as voice and text and Tableau Machine Algorithms which will surface recommendations for workbooks and data sources that are trusted, highly used and contextually relevant to individual workflows. The software is expected to be available "later next year."
2016 - Tableau acquired German startup HyPer to strike back at Zoomdata
BI giant Tableau has acquired HyPer, an early-stage German startup that has developed an advanced database technology. Tableau intends to incorporate the technology into its product set. Tableau is a business intelligence and analytics company, taking business data and helping companies make sense of it. The new HyPer database technology should provide a performance boost across Tableau products. Among the capabilities HyPer brings to Tableau include faster data analysis, regardless of the size of the data set; unifying the transactional and analysis systems (presumably to speed up those processes); richer analytics capabilities and support for structured or semi-structured data, which is increasingly important when processing Big Data sets.
2015 - Big Data analytics platform Platfora scores $30M
Platfora, a company that helps customers process and make sense of big data, announced a $30 million investment today. Platfora has been designed to work with big data (petabyte or larger) on a variety of platforms including Amazon Web Services, Microsoft Azure and Hadoop. It helps business analysts make sense of a variety of data sets without the help of data scientists or IT. At a basic level Platfora does three things: it prepares the data for analysis. It then processes the data in an in-memory database and perhaps most importantly it provides a visualization layer for business analysts and others to view the data in meaningful ways. Once IT has set up the platform, users can get to work exploring. The data prep and processing happens in the background as the analyst points to different sources to build a set of data they wish to work with. Once that process is complete, they can view the data in various ways in charts and graphs as you would expect.
2014 - Data Analytics service Tableau hits $100M per quarter revenue mark to win over Palantir
Data analysis and visualization company Tableau continues to grow at a fast pace, hitting the $100 million mark for the first time in the third quarter. Tableau is often viewed as the posterchild for next-generation analytics software and continues to add customers at a rapid pace. Despite its fast growth and innovative spirit relative to the legacy business intelligence and analytics business, though, there are lots of startups — and, now, even Salesforce.com — gunning to chip away at its growing marketshare. They have seen what Tableau did right in making data analysis a visual experience doable even by non-analysts, and are trying to make products that are bigger, faster, easier and/or cheaper. However, Tableau has lots of room to grow and the money to do it. The company claims to be investing more money than ever into research and development — and even has a dedicated R&D team — and in September showed off an early version of a new mobile product it’s calling Project Elastic.