The amended Unemployment Insurance Act (AVIG) marked the beginning of new era for the unemployment insurance business in Switzerland, Instead of passively managing unemployment statistics, the Swiss government is now executing a proactive labor market policy. The new principle of “reintegration before retirement” aims at a lasting reintegration of jobseekers into the labor market.
Up-to-date information and flexible analysis options are required for statistical observations, which are used for various purposes, such as short-term economic indicators or for controlling the correct execution of the Unemployment Insurance Act. At the same time, it must be possible to fine-tune analyses to the relevant question in every case. For this purpose, the Labor Market Statistics – a department of the Swiss State Secretariat for Economic Affairs (SECO) – had been operating a business intelligence system based on a traditional data warehouse.
Among the approximately 900 users are responsible federal offices, the employees of 120 regional offices (RAV) of the national employment service in the 26 Swiss cantons and more than 40 unemployment insurance funds. The result: A complex and heterogeneous user community with various requirements, reflecting the federal system of Switzerland.
Managing Performance Problems
Due to increasing requirements regarding labor market statistics, SECO initiated the LAMDA (Labor Market Data Analysis) project. A number of business intelligence applications were implemented for several purposes – for example, the official labor market statistics, the statistics of payments executed by unemployment insurers, the key performance index for regional office executives and an application for public information regarding unemployment. Many of these applications required complex calculations.
A more complex analysis requires a new infrastructure, as Dr. Elmar Benelli, Data Warehouse LAMDA Manager at SECO, explains, “We experienced increasing performance problems. With the existing infrastructure, such problems would have been manageable only with substantial effort and expenditures. The limiting factors were the physical separation of the database system and the data, as well as the data transport across the network, which is also used by other parties.”
Pivotal Greenplum Delivers Speed and Flexibility
As a new database solution to cover big data requirements, Pivotal Greenplum replaced the legacy database to handle all Swiss labor market statistics.
Pivotal Greenplum operates with massively parallel processing (MPP), offers flexible scalability and can be operated with various hardware platforms. Utilizing Pivotal Greenplum, the Swiss State Secretariat for Economic Affairs is now able to provide analyses to the user community faster and with greater flexibility.
“The cooperation of the team, comprising SECO employees and partners, as well as Pivotal was excellent,” says Benelli. “Pivotal Engineers stayed in touch constantly, were always available and reliably solved all problems that arose.”
“We experienced massive front end performance increases with Pivotal Greenplum. Even in case of complex queries, the results are displayed quickly,” Benelli confirms.
“Copying of the database now goes extremely quickly,” Benelli adds. “Previously, the preparation of a separate database for test and development purposes, or special analyses with high performance requirements, took the data warehouse team two weeks. With Pivotal Greenplum, all it takes is copying, which can be done in 20 minutes.”
Low Cost of Ownership
“Pivotal Greenplum provides the hardware flexibility we needed,” Benelli points out. “It enables operation on low-cost, industry-standard servers that can be easily acquired from the usual government suppliers. So we will remain flexible and independent of a specific hardware provider in the future as well. Other solutions we evaluated included proprietary components that would not allow such flexibility.”
The hardware flexibility and low total cost of ownership, coupled with the scalability and performance of Pivotal Greenplum, position SECO for a future in which big data will only grow bigger – enabling this government entity to seamlessly continue to deliver essential data to its user community.