The week of 2013 October 28 was a big one for Paxata, Inc. Founded in January of 2012, followed by advisories, beta customers also known as "Pax Pros", and 12 sprints, Paxata quietly released their first GA product in May of 2013. With panels and debuts at the Strata + Hadoop conference in New York and other events, leading up to announcements and demonstrations at the Constellation Connected Enterprise at the Ritz Carlton in Half Moon Bay, California, Paxata officially left stealth mode, publicly discussing:
- Five Blue Chip Customers: UBS, Dannon, Box, Pabst and $49 B High Tech Networking Manufacturer
- Partnerships with Tableau, QlikTech and Cloudera
- Adaptive Data Preparation Platform
- Eight Million US Dollars in the latest round of funding led by Accel
- Filling out the Management Team with Enterprise Software executives having backgrounds from SAP, Tableau and Hyperion
The most wondrous feature of the Paxata Adaptive Data Preparation Platform is how it adds semantic richness to one's data sets by automatically recommending and linking to third-party and freely available data. This allows one to bring in firmographic, demographic, social and machine data within the context of the user's goals. This is what truly allows the Paxata Adaptive Data Preparation Platform to go beyond data exploration and discovery.
Paxata has received a fair amount of press as well, some of which I've referenced below. However, all this press misses what is one of the most important additions Paxata makes to the toolboxes of Data Management & Analytics [DMA] professionals… the ability to present questions to the user that they may not have thought of on their own. Paxata was one of the companies that inspired my DataGrok blog post. Paxata was in stealth at the time, and couldn't be named then. Now, I'm happy to be able to write that Paxata is one of the few companies or projects building tools that allow the creator and user of data to go beyond data discovery, beyond data exploration, to being able to fully, deeply understand their data. Data discovery and data exploration tools allow one to determine if various data sets can answer the questions posed by business, engineering or scientific challenges. These tools go further by exposing data integrity issues among data sets or data quality problems within a data set. Some such tools might help the user find new data sets or how various data sources within an organization might fit together in a data warehouse. Some hark back to grep, sed and awk to parse textual data. Others provide probabilistic and statistical tools to determine the appropriate shape, distribution or density functions of a data set. But Paxata is one tool that does all these and more, and does it through your web browser in a collaborative fashion, maintaining the history of each collaborator's operations on the data sets.
When my partner, Clarise, and I were first briefed by Paxata in November of 2012, we were so excited that we stayed over three hours. The demonstration, of what was then a much rougher product than what you see today, incited both of us to exclaim how much we wished that we had this tool back in our DMA practitioner days. We were treated to a demonstration using the data from another Constellation Research customer with which we were familiar. Over a year later, we were treated to a pre-launch briefing using current data sets from that same customer. The ease of use, the pleasantness of the user experience, the simplicity with which one could complete complex tasks, from histograms to column-splitting, showed the maturity that Paxata had gained since our first exposure. What was most important to us, was that Paxata could show a solution for every need that we would like to see in the Adaptive Data Preparation Platform, drawing from our experiences in implementing data warehousing and business intelligence programs since 1996, as well as our decades of experience in computational statistics and operations research.
- Collect and parse data of disparate types and sources including XML, JSON, Excel, Flat Files and relational databases
- Pre-analyze and visualize the data sets
- Combine different data sets
- Separate data into patterns
- Verify individual datum for integrity, quality, mastering and governance
- Allow multiple IT and end-users to prepare and operate upon the data
- Maintain the history of what each user [a.k.a. Pax Pro] does, and show that history to all other users
It allows data warehousing and BI extract, transform and load professionals, business analysts, data scientists, chemists, physicists, engineers, researchers, and professionals of all skills who work with data to completely understand and resonate with their data sets. The Paxata Adaptive Data Preparation Platform does what few other tools can do, it provides clues to what you didn't know to ask. It poses questions that the data can answer, but that you didn't think to ask. And it does all of this in a familiar looking interface, in HTML 5, in your favorite web browser, wherever you are, whenever you need it. In Paxata's words:
Paxata pricing is published and open. There are three subscriptions available:
- Pax Personal
- Pax Share
- Pax Enterprise
Each of the Paxata subscriptions build upon the first, from an individual subscription to the ability for those with individual subscriptions to share in a single environment, to a full organization-wide subscription. Of course, what makes this possible, is that the Paxata Adaptive Data Preparation platform is available as a Cloud service, accessible through any modern HTML 5 web browser whether that's from a sophisticated, high-end workstation, a tablet or smart phone.
The main value comes not from a nice-looking, fairly intuitive interface, but from the underlying technologies that makes Paxata so useful: powerful Mathematics, Semantics and Graph Theory algorithms. The results of which are easily accessible through this Cloud-based, web experience, while the complexities are under the covers, not getting in the way. This fact is what makes the Adaptive Data Preparation Platform so accessible to business analysts, and other creators and users of data who are not PhD statisticians. Paxata uses proprietary algorithms that detect relationships among data sets, using probabilistic techniques to select the best joins, semantically typing the data so that it can intelligently enrich the data, clean the data and merge the data based upon context not just metadata. All of this is done in an ad hoc fashion, with no predefined models or schæmas needed. These proprietary algorithms make use of
- Latent Semantic Indexing
- Statistical Cluster Graphing
- Pattern Recognition
- Text Analytics
- Machine Learning
Distributed computing and in-memory technologies allow these computational statistics algorithms to be,cost effectively executed in parallel, across massive data sets. Coupled with the advancements in visualization technologies, Paxata is able to address a 13.5-16 Billion dollar market over next three years, with extremely attractive pricing. The true return on investment from Paxata comes from flipping the DMA equation around. Currently, a common truism is that 80% of the time on a DMA, Data Science, DW or BI project is spent in preparing data; 20% in analyzing the data. Paxata reduces that data preparation percentage, such that 70% is analytics, 30% is preparation. This reduces not only the labor directly involved in preparing the data, but also allows an Agile framework to address significant business needs at the right time, in a sustainable fashion.
Paxata's strategy is to attach to the QlikView and Tableau markets that are being hampered from enterprise adoption because of these very data preparation challenges. Along with these partnerships, is the partnership with Cloudera, providing enterprise class access to modern, distributed data storage systems. Add connectors to common enterprise and external data sources and the third-party Paxata Enrichment Libraries, and it is obvious to the most casual observer that the Paxata Adaptive Data Preparation Platform addresses the most frustrating complaint of Data Scientists and Business Analysts alike: that too much of their time is spent on plumbing, whether directly or waiting for IT. We have long spoken about the need for IT to give up control of data, and realize that their most effective role is to provide a framework of success for end-users to fully, deeply understand and use their data to solve real problems. Paxata creates this framework for success.
Other Sources to learn about the Paxata launch:
- The Paxata Web Site
- Diginomica: Can Business Users control their data destiny? Paxata says yes
- GigaOM: With $10M from Accel, Paxata wants to make data prep a breeze
- VentureBeat: Paxata grabs $8M to help data scientists skip the dirty work
- YouTube: Paxata Customers and Partners Help Launch the Company
- YouTube: The Cube: Prakash Nanduri - Big Data NYC
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