In today’s business environment, data volumes are growing. At the same time, data latencies are shrinking as BI and analytics initiatives flourish. To support business decision-making, users demand fresh and accurate data that’s available where and when they need it, often in real-time. As business analysts try to run reports, many organizations find that their production databases are overloaded. A common solution is to offload production data to a secondary database which is used by operational reporting applications. This approach can only be successful, however, when updates to the reporting server are done rapidly.
In industries like retail and hospitality, the company headquarters must pull up-to-date information from remote sites, like stores or hotels, to facilitate company-wide reporting and analytics. Data synchronization may be done over the Internet or another form of wide area network with low bandwidth and poor performance. To facilitate business, data must be transferred quickly.
More and more organizations are also exploring cloud-based analytics. Since the link between data centers and the cloud is usually low-bandwidth, it is essential to use a data integration tool that sends information rapidly.
Business and Technology Challenges
As each of these trends evolve, companies are realizing that traditional bulk processing of data simply isn’t meeting their business or technology needs.
The inability to meet low-latency data warehousing requirements dramatically reduces the value of BI and analytics tools. When IT cannot provide business users with fresh information, it inhibits organizations from using BI and analytics more widely.
Using batch processes for loading data warehouses creates operational complexity. Managing large schedule batch windows means more overhead for the IT team, as well as greater demands on the technical infrastructure in terms of CPUs and memory. In addition, using ETL products to facilitate real-time data movement usually results in labor intensive processes and workarounds.
How Attunity Can Help
A promising solution is to change the processing paradigm and only work with information that has actually changed in the database. This paradigm is based on change data capture or CDC. Since daily changes often represent only a fraction of the total data volume, CDC products like Attunity Replicate greatly improves efficiency.
Remember - not all CDC tools are created equal. Some use agents on the database servers, while others use stored procedures. Both approaches negatively affect database performance. Attunity Replicate takes a different approach – it drives the data change function off the database log, which means it doesn't interfere with the database server or add to its load. In addition, Attunity TurboStream CDC is designed to significantly enhance data delivery performance and helps improve strategic initiatives including Big Data analytics and business intelligence (BI).
Attunity Replicate is simple for IT teams to install and learn, and quick to configure and test. That means lower total cost of ownership for the organization, more time for the IT team, and more satisfied business users.