Category Archives: Uncategorized

Liliendahl on Data Quality

As reported in the post Fighting Identity Fraud with Identity Fraud and experienced with the post 255 Reasons for Data Quality Diversity I have seen several sloppy attempts of link building from SEO agencies working for data quality tool vendors.

The other day it happened again, this time on LinkedIn.

There was a comment in the Master Data Management Interest group:

DataLadder SEO

The comment is now deleted by the author and I do understand why.

I guess a SEO guy was working for Simon at DataLadder and Nathan from somewhere else at the same time and given access to their LinkedIn accounts. However he/she posted a comment to be meant being from Simon logged in as Nathan (who is not working with MDM and data quality).

So, data quality tool and service vendors: You can’t fight identity fraud with identity fraud and you can’t advocate for a single view of…

View original post 12 more words

Gigaom

Back in the middle of last year, a clever little service called doo went into beta on OS X and Windows 8, which was itself only a consumer preview at that point. The service allowed users to import all the documents they had in various cloud storage pockets ––DropBox, Google Drive and email accounts — and bring them together in one place, where they could be automatically scanned, tagged and categorized.

Doo OCRNow doo is coming out of beta on OS X(s aapl) today and, over the next few weeks, on Android(s goog), then iPhone, then iPad (a refreshed Windows(s msft) 8 app will follow in the next couple of months). And, while the end result is similar to that in the beta, it’s quite a different beast under the hood.

Why? As CEO Frank Thelen told me, the future may be all about semantic tagging, but for now people still…

View original post 328 more words

Top Technology Trends

Cloud based Business Intelligence (BI) is widespread today and is being used by many organizations globally. It is a revolutionary concept of delivering business intelligence capabilities “as service” using cloud based architecture that comes at a lower cost yet faster deployment & flexibility. Software as a Service (SaaS) BI is also being used by many small and medium sized enterprises who seek to speed up their businesses with BI and analytics tools.

According to a recent 2012 Wisdom of Crowds Cloud Business Intelligence Market Study of 859 respondents, there is a current strong investment in cloud based BI and growing interest in tapping into the cloud’s benefits; while a Gartner survey throws the fact that almost one-third of the BI platform users surveyed (27 percent, to be exact) are using or planning to use the cloud / SaaS model to expand their business intelligence capabilities in the next 12 months…

View original post 376 more words

Data dünyasında gelecek konseptler

Gigaom

Database startup Citus Data on Tuesday joined those trying to enable fast SQL queries on Hadoop data, but it has much larger goals. It thinks it can be the only analytic database that anyone needs, able to query data wherever it’s stored across a company’s environment — in relational databases, Hadoop, MongoDB, Amazon (s amzn) S3 and elsewhere.

Big data has opened companies’ eyes to the importance of analytics and alternative data stores, but combining the two often means learning new languages, using multiple tools and probably sacrificing the performance they’re used to from analytic platforms.

Citus Data’s flagship product, called CitusDB, is actually built atop PostgreSQL and its first iteration was designed for Google Dremel-like scale and speed on relational data. Thanks to a feature called “foreign data wrappers,” though, it’s able to run SQL on numerous data types (e.g., CSV, log and JSON files) that don’t comport with…

View original post 525 more words