With the maturing and ever increasing acceptance of the cloud across multiple industries and the data gravity gradually moving to the cloud, i.e. more data being generated in the cloud, we are seeing some interesting cloud-based data and analytics platforms offering unique capabilities. Some of these platforms could be disruptive to the established market leaders with their innovative thinking and ground up design that is “born in the cloud and for the cloud.”Read more
Tag Archive for: Data Warehouse
The simple truth about data warehouses is that the traditional “big bang” method of building them doesn’t work for most organizations anymore. The diversity of data sources and formats we can access is constantly expanding, and taking them all on at once to form a single central repository results in a massive project that can take years to show value. That doesn’t mean we should throw out the concept of data warehousing altogether, though. In fact, there’s a better way to do it that is built on proven development practices, provides value as you go, and feels like less of a massive undertaking: an iterative data warehouse. Read more
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. Read more
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 data discovery approach produces insights very quickly, but it also encounters challenges when dealing with data transformation. Most data discovery tools are limited in their ability to manipulate data. Additionally, understanding relationships between different data entities can require expertise that some users may not possess. In order to enable agile data discovery, organizations need agile data warehousing. Read more
Don’t think you have big data? Chances are you do. The fact is if you have a website, you have big data. Web servers capture and store events related to user traffic. The web logs they generate essentially tell the story of what users did when they visited your site. This information can provide your organization with extreme business value.
If you think you have big data to analyze from your website, you may want to look into Apache Spark. It’s easy to get started with and makes short work of analyzing your web logs. It’s actually pretty fun to work with, too. If you enjoyed playing with LEGOs as a kid, you may have a childhood flashback with Spark. Read more
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 strategies remains reliable and responsive on a daily basis. Read more
On September 24th, Ironside hosted a webinar on Exploring Data Warehouse Strategies. You will hear from our experts on different data warehouse strategies for traditional and emerging solutions. Whether traditional, hybrid, or cloud-based, this webinar will give you insight on finding the best data warehouse option for your business. Read more
In 2014, cloud data warehousing services led the information management category in increased adoption rate, jumping from 24% to 34% according to surveys by Information Week . For organizations challenged by data urgency needs that can be difficult to meet with traditional data warehouse infrastructures, cloud services offer an alternative that can provide value at the pace of business, often supplementing existing, on-premise data warehouses. With new technologies and advancements in the cloud data warehousing space, 2015 should prove to be an exciting year for those looking to build out or implement new cloud based DW programs. Whether you are in the midst of a cloud DW initiative, looking to start one soon, or just getting to know the technology – the five trends that we will discuss below are items you will want to keep in mind for the coming year. Read more
Cognos makes extensive use of data warehousing concepts. Most data warehouses are built using dimensional modeling techniques (also known as the “Kimball style”). Data is divided into fact and dimension tables, which are joined together in star schemas. Restructuring data in this fashion takes a great deal of effort, both in planning and implementation. These types of changes are only done because they are necessary for high-quality analytics. Understanding more about how they work and why they are important can help make Cognos a more efficient and effective reporting tool. Read more
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 has a purpose-built analytics engine and an integrated database, server, and storage. With simple deployment, out-of-the-box optimization, no tuning, and minimal ongoing maintenance, the IBM Netezza data warehouse appliance has the industry’s fastest time-to-value and lowest total cost of-ownership. Read more