The explosive growth of cloud computing has completely changed the way we approach data warehousing. This transition has resulted in obsolescence for traditional data warehousing solutions like IBM’s Netezza, as their data processing approach became unfeasible in large datacenter environments.
Netezza used a specialized type of processing hardware called field-programmable gate arrays (FPGAs), which could be configured to perform incredibly niche computing tasks at the expense of broader functionality. With the public/private cloud, specialized hardware like this was challenging to manage, eventually forcing IBM to classify Netezza as an end of life (EOL) solution in 2019. If you were one of the businesses using Netezza, searching for a new solution to get full vendor support and more modern functionality would be on top of your list.
As with any data warehouse migration, you will have to overcome a few stumbling blocks related to platform compatibility and data transformation, among others. Let’s see them in detail.
Syntax and querying issues – Netezza uses a proprietary augmented fork of the traditional structured query language (SQL), meaning most of your existing query templates and operating procedures will be either inefficient or incompatible after migration. Netezza SQL was built to run in tandem with its FPGA hardware acceleration units, and modern alternatives will not consider it, forcing you to reassess and redevelop your database as you migrate.
We can alleviate these worries with our proprietary Evove application, which is capable of automatically converting approximately 95% of legacy data definition language (DDL) SQL queries and stored procedures to your new Azure data warehouse. For any DDL, SQL queries and processes that cannot be automatically converted, our dedicated team of data warehousing engineers can rewrite and remediate incompatibilities to achieve full operational functionality on your new data platform.
Adhering to timescales and budgets – When proposing a new data warehousing system, you must communicate your expected timescales and budgetary requirements. With traditional systems like Netezza, it can be difficult to accurately approximate migration timescales, which can lead to an increased fiscal impact. Unforeseen circumstances like data incompatibility, ETL failures and accidental data loss can result in extra staff hours to stabilize the platform further.
With our proprietary Evove application, you can minimize the risks associated with your data warehouse migration. We use templates to streamline data ingestion to your new data warehouse. This allows us to determine timescales for migration proactively and improve visibility into data incompatibility during the load stage, so you can better communicate timescales to key stakeholders across the business.
Optimizing datasets during migration – With newer data warehousing platforms, a lot of redundant data from your traditional solution can be removed, without any value loss. Data redundancies can increase migration timescales, storage requirements and slow down data processing on your new system.
Evove tackles this problem with Lineage Optimizer. Before data translation occurs, Lineage Optimizer will trace all data columns on your legacy platform. This process will uncover redundant data that can be removed during translation, improving the optimization of your new database and reducing operating costs. After the translation is complete, Lineage Optimizer will continue to audit data on your new platform. This will benefit data governance in the long-term, helping you maintain compliance with regulations like GDPR, CCPA and PCI-DSS.
Trianz is a leading data warehousing consulting firm with decades of experience in helping our clients keep pace with new developments in data warehousing. Our dedicated team of data warehousing engineers will work closely with you to assess your existing database before applying our Evove application to streamline the entire migration process. Schedule a consultation with us today!
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