Discover Top Posts Tagged with #infinit.e

Performing semi-structured and structured data analysis

Although IKANOW is squarely focused on handling unstructured data discovery (by helping make it semi-structured) and analysis needs we understand that there is a need to fuse that information with more structured sources. In researching and developing this capability our engineering team has created a framework and set of tools specifically designed to handle structured information. It allows users to connect to and make sense of databases in a very similar way to how we handle unstructured data. Guess here might be the "so what" moment.

Infinit.e excels at handling the ingestion and enrichment of unstructured data (RSS, ATOM, news feeds, blog postings, documents etc.) but this ability allows for the handling of structured data found in relational database systems such as: SQL Server, Oracle, MySQL, PostgreSQL, etc, delimited files such as: CSV, tab delimited, etc, and XML documents. This provides organizations with a holistic data analysis platform that can easily harvest most any type of information.

With unstructured data the Infinit.e tool set has a framework and is designed to allow for quick integration with popular text extraction tools and natural language processing technology that is cloud based, open source, commercial off the shelf or government off the shelf to find entities, events, facts, summaries, quotations and sentiment buried within text. Structured data presents a little different of problem since these relationships are already contained.

The engineers at IKANOW have developed a simple to configure data extraction interface and framework that allows you to:

Connect and harvest information from any JDBC compatible RDBMS system

Harvest file sources from a filesystem

Parse XML documents and fuse with other structured and unstructured data sources

Map data elements in a structured source to corresponding entities and events

And specify advanced internal data processing functionality using JavaScript

This functionality provides an extremely powerful framework, engine and fusion capability to merge a wide variety of structured and unstructured data sources into single unified analysis environment. - C.V.

#structured data #unstructured data #infinit.e #harvesting #enrichment #engineering #development

Performing Market Research with the Infinit.e Beta

Recently we began to look at how Infinit.e could be used to perform Competitive Intelligence Research (Market Research) as well as Brand Monitoring. Businesses today are in need of tools that enable quick insight into the competitive market landscape. Information about competitors and products play a big role in how effective your business is and can become.

The web has changed the way companies conduct themselves as well as the way individuals conduct themselves. Social Media has enabled people to voice themselves in a way that was not previously available and with that comes a powerful tool that can impact your business, product or brand in both positive and negative ways.

Infinit.e enables businesses and individuals to perform competitive intelligence across markets and learn from trends and patterns shown by historical activity. This enables businesses to gain insight and learn from competition by using the available media and information that is produced on the internet daily. Businesses can also gain competitive advantages by gaining insight into patterns and trends pertaining to products and services offered in the market. Social Media takes many forms and has a wealth of knowledge contained in the form of blogs, forums and social networks to look for events, facts and summaries along with the sentiment of the language.

The short video below illustrates an example of using Infinit.e to research news pertaining to tablet computers and, more specifically, buzz pertaining to the operating systems in the discussed media and by product vendors. We do this by looking at some specific statistics (significance) to identify patterns and temporal aggregations to visualize what is happening in the technology landscape.

Sentiment adds an interesting dimension to competitive intelligence research. We are currently hard at work in integrating sentiment data into our data model and this will offer a new look at how organizations can manage their brand and fuse that information with other media sources to get an analytic picture of their competitive landscape. This capability will be coming later this summer. This capability will allow organizations to follow who is talking about your business or products and identify the sentiment of the discussion taking place over time. You will able to view analytics that will allow monitoring of the buzz generated from a product launch or monitor your brand against social network data.

We are super excited about using this technology to assist in the Market Research vertical and the value it can provide. We also plan to put together additional use cases against specific events and products to illustrate additional functionality and uses.

If you are interested in the topic like the above and would like to help us shape the growth of an open analytical environment please send us a note or join our user forums.

-CM

#market research #infinit.e #beta #analytics #branding #corporate monitoring #whitepost #patterns #trends #technology

As time marches on (beta progress)

We have been making significant progress as we move toward our general availability and beta release scheduled for later this summer. We plan to incrementally release throughout the summer using our agile process but will provide a major release as part of the final process.

As we start to get closer to this major release we will be providing updates via our blog outlining new functionality and features as well as providing tutorials support through our support environment.

There will be major enhancements throughout the Infinit.e environment including enhancements to the data layer, api and user interface (UI) and user design (UX). We are super excited on what value these improvements will provide to our open and extensible knowledge discovery platform.

We would also like to thank all of our partners that have been participating in a Open Innovation approach during our ALPHA process to help shape the future of this capability.

Now for some of the anticipated new capabilities and features. You might of seen some of the previous videos illustrating the timeline and geospatial visualizations for alpha. Major improvements are currently ongoing. The video sample below illustrates some of the latest improvements that we will be pushing out shortly.

Some of the anticipated improvements that will be coming this summer. As new information becomes available we will push it out here on blog and provide tutorials on our support environment.

A more feature rich API layer (including aggregations)

Database harvesting using JDBC

Fileshare harvesting using CIFS

Data model improvements

Full text query engine enhancements

Geospatial filtering engine enhancements

Temporal filtering engine enhancements

Communities

Source management

Event support

Improved filtering at the widget and system level

Advanced query tools and customization

Ability to save and re-run queries

Enhanced widget framework and plug-in

Enhanced plug and play enrichment

These are just some of the upcoming improvements to the toolset and framework. We will outline these in greater detail as we move throughout the summer and post updates here on on our website and support environment as these features start to become available.

If you are interested in learning more about the new features and changes coming in beta and would like to help us shape the growth of an open analytical environment please send us a note or join our user forums.

#beta #ikanow #infinit.e #features #software #infrastructure #improvements #GA

Video example illustrating how to update your IKANOW profile.

#video #tutorial #profile #infinit.e #update #account

Video illustrating how to use the Infinit.e Radar Widget

#infinit.e #video #tutorial

Metadata Tools (Part II)

At the start of beta our development focus has somewhat changed with regards to metadata and harvesting. Up till now we have been focused purely on using entity information to drive the engine. In beta we are starting to pull in event information and sentiment. These additions provide us with additional ways to add statistical algorithms to slice and dice the data.

Events provide us with greater levels of context. This provides us with ways to view datasets differently as well as different ways to look how to query the information. Users will now be able to query based on event types and event context further expanding the query engine of the toolset and API.

In addition sentiment is also be extracted and applied to the metadata. This provides insight on the tone of language and can be use statistically to delivery insights into whether or not a statement is made with positive or negative tone.

#infinit.e #metadata #whitepost

Widget Loader example video widget-loader-overview-I.mp4 (via IKANOW)

#alpha #infinit.e #tutorial #video #widget

Here is quick video example on how to use the Infinit.e Dimension Explorer - dimension-explorer-overview-I.mp4 (via IKANOW).

#alpha #tutorial #video #infinit.e #query