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In short, I found the data setup to be simple and straightforward and well-suited to the typical business analyst's skill level as well as within the reach of most other business users. That may be a major shortcoming for some users. It cannot be used for any use case that requires actual real-time, streaming analysis. That will suffice for many use cases and certainly for the use cases IBM is aiming for: visualization, patterning, and social media point-in-time analysis. However, in IBM Watson Analytics, data can be refreshed frequently, as often as every 5 seconds or so, for a near-real-time read. Note that IBM Watson Analytics does not do streaming analytics such is common with the Internet of Things (IoT) data and other sources and systems where information is streamed and analysis must be instant. Either way, the data sets shown there can come from user uploads, data accessed through one or more IBM Watson Analytics' connectors, data sets that have been combined by the user within the system, or data sets from IBM Watson Social Media (a social media analytics tool accessible from within the IBM Watson Analytics tool). The simplicity in this makes it easily undervalued when you consider that data prep typically takes more time than any other step in the analytics processes-yet here it is a matter of prompts and clicks and you're done.Īfter all data sets are added by the user or IT department, the user interface (UI) shows the data sets in the user's choice of icons or a table. The system prompts the user with suggested cleaning and prep tasks that particular data set appears to the system to need. In other words, "Shape Before" lets user easily clean and prep the data with just a few clicks prior to running an analysis on it. I used the "Shape Before" button to move through the data and delete empty rows, but you can also clean up addresses and dates and other information to achieve conformity which aids in the analysis. Users can depersonalize customer names and other personally identifiable information (Opens in a new window) (PII) to comply with privacy rules in the "Shape Before" function prior to upload. Users can also shape and cleanse the data prior to uploading it by clicking the "Shape Before" button rather than the "Upload Now" button, which are both choices after clicking "+ New data" (the Add Data button) on the IBM Watson Analytics homepage. Users are then prompted on setting rules. However, users can easily load data themselves providing they have the credentials to access it.
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While this is a full self-service BI tool, IT can lend a hand in loading company data to simplify things further for business users and to also ensure compliance and security rules (Opens in a new window) are set as IT would have them. IBM Watson Analytics also lets you directly query a variety of databases including Cloudera Impala, Microsoft Azure ($14,300.00 at Microsoft Azure) (Opens in a new window), MySQL, Oracle, PostgreSQL, PostgreSQL on Compose, Structured Query Language (SQL) Server, Sybase, Sybase IQ, and Teradata. This is where I found numerous connections to all social media (including Facebook, of course) as well as to blogs, comments, forums, and videos throughout the social media realm. It's interesting that IBM Watson Analytics lists a Twitter connector for use, but users must access IBM Watson Social Media for the rest of the social tools. (Opens in a new window) Read Our Chartio Review
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IBM Watson Analytics gets our Editors' Choice designation along with Microsoft Power BI and Tableau Desktop. The assistant serves the roles of both servant and guide for users with varying levels of data science and data visualization expertise. When you start using IBM Watson Analytics, it's clear that the machine learning (ML) and artificial intelligence (AI) behind it is an impressive accomplishment. Its highly advanced analytics engine works with a stellar natural language querying platform to make BI as easy to learn as it is powerful.
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All of the buzz is deserved because this application is a winner with its technical capabilities.
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IBM Watson Analytics (which begins at $30 per user per year for the Plus edition) has gained wide recognition in the self-service business intelligence (BI) space thanks in part to an ever-present marketing campaign.
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