Category Archives: Application ILM
Most application owners know that as data volumes accumulate, application performance can take a major hit if the underlying infrastructure is not aligned to keep up with demand. The problem is that constantly adding hardware to manage data growth can get costly – stealing budgets away from needed innovation and modernization initiatives.
Join Julie Lockner as she reviews the Cox Communications case study on how they were able to solve an application performance problem caused by too much data with the hardware they already had by using Informatica Data Archive with Smart Partitioning. Source: TechValidate. TVID: 3A9-97F-577
Adopting SAP HANA can offer significant new business value, but it can also be an expensive proposition. If you are contemplating or in the process of moving to HANA, it’s worth your time to understand your options for Nearlining your SAP data. The latest version of Informatica ILM Nearline, released in February, has been certified by SAP and can run with SAP BW systems running on HANA or any relational database supported by SAP.
Nearlining your company’s production SAP BW before migrating to a HANA-based BW can provide huge saving potentials. Even if your HANA project has already started, Nearlining the production data will help keep the database growth flat. We have customers that have actually been able to shrink InfoProviders by enforcing strict rules on data retention on the data stored in the live database.
Informatica World is around the corner, and I will be there with my peers to demo and talk about the latest version of Informatica ILM Nearline. Click here to learn more about Informatica World 2013 and make sure you sign up for one my Hands On Lab sessions on this topic. See you at the Aria in Las Vegas in June.
In my previous blog, I explained how Column-oriented Database Management Systems (CDBMS), also known as columnar databases or CBAT, offer a distinct advantage over the traditional row-oriented RDBMS in terms of I/O workload, deriving primarily from basing the granularity of I/O operations on the column rather than the entire row. This technological advantage has a direct impact on the complexity of data modeling tasks and on the end-user’s experience of the data warehouse, and this is what I will discuss in today’s post. (more…)
Column-oriented Database Management Systems (CDBMS), also referred to as columnar databases and CBAT, have been getting a lot of attention recently in the data warehouse marketplace and trade press. Interestingly, some of the newer companies offering CDBMS-based products give the impression that this is an entirely new development in the RDBMS arena. This technology has actually been around for quite a while. But the market has only recently started to recognize the many benefits of CDBMS. So, why is CDBMS now coming to be recognized as the technology that offers the best support for very large, complex data warehouses intended to support ad hoc analytics? In my opinion, one of the fundamental reasons is the reduction in I/O workload that it enables. (more…)
Columnar Deduplication and Column Tokenization: Improving Database Performance, Security and Interoperability
For some time now, a special technique called columnar deduplication has been implemented by a number of commercially available relational database management systems. In today’s blog post, I discuss the nature and benefits of this technique, which I will refer to as column tokenization for reasons that will become evident.
Column tokenization is a process in which a unique identifier (called a Token ID) is assigned to each unique value in a column, and then employed to represent that value anywhere it appears in the column. Using this approach, data size reductions of up to 50% can be achieved, depending on the number of unique values in the column (that is, on the column’s cardinality). Some RDBMSs use this technique simply as a way of compressing data; the column tokenization process is integrated into the buffer and I/O subsystems, and when a query is executed, each row needs to be materialized and the token IDs replaced by their corresponding values. At Informatica for the File Archive Service (FAS) part of the Information Lifecycle Management product family, column tokenization is the core of our technology: the tokenized structure is actually used during query execution, with row materialization occurring only when the final result set is returned. We also use special compression algorithms to achieve further size reduction, typically on the order of 95%.
I was at an IT conference a few years ago. The speaker was talking about application testing. At the beginning of his talk, he asked the audience:
“Please raise your hand if you flew here from out of town.”
Most of the audience raised their hands. The speaker then said:
“OK, now if you knew that the airplane you flew on had been tested the same way your company tests its applications, would you have still flown on that plane?
After some uneasy chuckling, every hand went down. Not a great affirmation of the state of application testing in most IT shops. (more…)
I’ve been approached by a number of customers who are looking to archive data from their Salesforce application. There are two primary drivers I have heard cited:
- The need to manage the retention of Salesforce data and easily find and access it for legal eDiscovory
- Storage cost reduction for data that’s no longer active
The OAUG hosted its annual convention, Collaborate13, this week in Denver, Colorado. The week started out with beautiful spring weather and turned quickly into frigid temperatures with a snow flurry bonus. The rapid change in weather didn’t stop 4,000 attendees from elevating their application knowledge in the mile high city. One topic that was very well attended from our perspective was the evolution of database archiving. (more…)
Businesses retain information in an Enterprise data archiving either for compliance – adhere to data retention regulations – or because business users are afraid to let go of data they are used to having access to. Many IT have told us they retain data in archives because they are looking to cut infrastructure costs and do not have retention requirements clearly articulated from the business. As a result, enterprise data archiving has morphed into serving multiple purposes for IT –they can eliminate costs associated with maintaining aging data in production applications, allow business users to access the information on demand, all while adhering to some – if any known or defined – retention policies. (more…)
Proactive performance management of systems and applications has always been an elusive goal for many organizations. We have enough fires to fight and issues to deal with in our day to day life to make searching for performance problems rank somewhere just below defragging our hard drives. At Informatica we talk with companies every day that try to manage their application performance proactively but lack the tools or process to make it happen. In this blog we will talk about the five keys to making proactive performance a reality. (more…)