Data Warehousing

15 Feb 2017

Understanding Data Governance: Tools, Documents, Processes, and People

By | February 15th, 2017|Categories: Advisory, Business, Information Management|Tags: , , , , , , , |

Data governance is a common need across organizations, and can be a very challenging subject to tackle. Understanding data governance's components, what good governance looks like, and the drivers behind adopting it is essential to creating a successful governance effort. What Is Governance? Governance (more specifically, data governance) is a discipline for managing all aspects [...]

21 Jun 2016

Agile Data Warehousing with Spark

By | June 21st, 2016|Categories: Information Management, Infrastructure, Strategy & Innovation|Tags: , , , , , , |

Data discovery is a “new” technique that takes a less formal and more agile approach to analyzing data. Okay, well, it’s not really new -- people have been doing this with spreadsheets for decades -- but the products that support it have improved greatly and have forced a more formal consideration of these techniques. The [...]

20 May 2016

Geoff Speare Named Information Management Practice Lead

By | May 20th, 2016|Categories: Awards & Recognition, Information Management, Press Releases|Tags: , , , , , |

Ironside has placed the reins of our information management and data integration practice into the hands of one of our strongest data handling experts: Geoff Speare. Geoff will now be serving in a broader strategic and management capacity as our Practice Lead for Information Management. His deep expertise across both traditional and big data-oriented infrastructures, passion [...]

1 Dec 2015

Industry Case Study: Modernizing the Data Warehouse for Finance IT

By | December 1st, 2015|Categories: Case Studies, Information Management, Newsletter|Tags: , , , , , |

As you've seen in some of our previous articles about the financial services industry, there's a lot that goes on behind the scenes to enable financial services firms to gain new customers and provide accurate investment advice.  What matters most, though, is that the technology powering all the fund transactions, client correspondence, market analytics, and sales [...]

1 Dec 2015

IBM Fluid Query and the Modern Data Warehouse

By | December 1st, 2015|Categories: Information Management, Newsletter, Strategy & Innovation|Tags: , , , , , , |

The modern data landscape is so much more diverse than it was in the past, and the modern data warehouse needs to increase its flexibility to keep up. In the modern warehouse, it’s not enough to just source all the data; it’s equally important to source all data types as well. Data professionals need to [...]

1 Mar 2015

ETL vs. ELT – What’s the Big Difference?

By | March 1st, 2015|Categories: Advisory, Information Management, Infrastructure|Tags: , , , , |

ELT is a term heard increasingly in today’s analytic environments. Understanding what it means, and how you can make use of it, requires understanding the traditional nature of how data warehouses are loaded and how data movement tools work. That's why we've pulled this article together: to break down the ETL vs. ELT divide and [...]

1 Oct 2013

Netezza – Design Best Practices & Guidelines

By | October 1st, 2013|Categories: Advisory, Information Management, Proven Practices|Tags: , , , , , , |

Today’s big data challenges for both transactions and analytics are increasing demands on data systems. Traditional data warehouses sometimes struggle as they are often NOT designed to meet the demands of advanced analytics on big data. That's where solutions like Netezza come in. IBM PureData for Analytics (formerly Netezza) is a data warehouse appliance that [...]

21 Oct 2010

Database Suitability Assessment and IBM Cognos Framework Manager Best Practices

By | October 21st, 2010|Categories: Modeling, Proven Practices|Tags: , , , , |

As consultants, we have found that the majority of struggling IBM Cognos implementations we encounter are due to either poor framework model design, or more often, a flawed database architecture. The case of the latter can present itself in a number of ways, but in the worst cases, we’ve discovered reporting applications built upon highly normalized OLTP systems that are ineffective and detrimental to both analytical and operational performance of an organization’s information systems. Another common case is an implementation of Cognos upon an existing data warehouse where users are provided with unfettered ad-hoc access to the data source for the first time, exposing previously unforeseen or unknown data quality issues. […]

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