A Perfect Storm?
As more of the tasks required of DBAs become more automated, the DBA will be freed to expand into other areas. So one front on this storm is the autonomic computing initiatives that automate DBA tasks. At the same time, IT professionals are being asked to know more about the business instead of just knowing the technology. So DBAs need to understand the business purpose and definition of the data they manage, as well as the technological underpinnings of the DBMS. The driving force here is predominantly regulatory compliance. This second front of the perfect storm will cause DBAs to work more closely with metadata to drive database archiving, data auditing, and security to ensure their organization complies with regulations like Sarbanes-Oxley, HIPAA, and others.
Regarding the wireless aspect of things, pervasive devices (PDA, handhelds, cell phones, etc.) will increasingly interact with database systems. DBAs will need to get involved there to ensure successful data synchronization. And database systems will work with disconnected data seamlessly, such as data generated by RFID tags.
Yet another big database trend is technology "suck." By that I mean the DBMS is as it sucks up technologies and functions that previously required you to purchase separate software. Remember when the DBMS had no ETL or OLAP functionality? Those days are gone. This will continue as the DBMS adds capabilities to tackle more and more IT tasks.
Another trend impacting DBAs will be a change in some of their roles as more and more of the recent DBMS features actually start being used in more production systems.
The net result of this perfect storm of changes is that data professionals are absolutely being required to do more... sometimes with less (less time, less money, less staff, etc.)
If you know the technology but are then required to know the business, this is doing more – much more. But the technology, in many cases, is also expanding. For example, DB2 9 incorporates native XML. Most DBAs are not XML savvy, but increasingly they will have to learn more about XML as the DBMS technology expands. And this is just one example.
Additionally, data is growing at an ever-increasing rate. Every year the amount of data under management increases (some analysts peg the compound annual rate of data growth at 125%) and in many cases the number of DBAs to manage that growing data is not increasing, and indeed, could be decreasing.
And, budgetary limitations can cause DBAs to have to do more work, to more data, with less resources. When a company reduces budget but demands more work, automation is an absolute necessity. Turning work over to the computer can help (although it is unlikely to solve every administrative issue). Sometimes IT professionals fight against the very thing they excel in – that is, automating work. If you think about it, every computer program is written to automate someone’s work – the write (word processing), the accountant (financials, payroll, spreadsheets), and so on. This automation did not put the executives whose work was automated out of a job; instead it made them more efficient. Yet, for some reason, there is a notion in the IT industry that automating IT tasks will eliminate jobs. You cannot automate a DBA out of existence – but you can make that DBA’s job more effective and efficient with DBA tools and autonomic computing.
And the sad truth of the matter is that there is still a LOT more than can, and should, be done in most companies. We can start with better automation of DBA tasks, but we shouldn't stop there!
Corporate governance is hot – that is, technologies to help companies comply with governmental regulations. Software to enable archiving for long-term data retention, auditing to determine who did what to which piece of data, and security to better protect data are all hot data technologies right now. But database security need to be improve and technologies for securing and auditing data need to be more pervasively implemented.
Metadata is increasing in importance. As data professionals really begin to meld together technology and business, they find that metadata is imperative. But most organizations do not have a metadata repository fully-populated and up-to-date that acts as a lexicon for business data.
And finally, something that isn’t nearly hot enough is data quality and integrity. Tools, processes, and database options that can be used to make data more accurate and reliable are not implemented appropriately with any regularity. So the data stored in our corporate databases is suspect. According to Thomas C. Redman, data quality guru, poor data quality costs the typical company at least ten percent (10%) of revenue. That is a significant cost! Data quality is generally bad in most organizations – and more needs to be done to address that problem.
With all of these thoughts in mind, are you prepared to weather this perfect storm?