The explosion of data and fast-changing customer needs have led many companies to a realization: They must constantly improve their capabilities, competencies, and culture in order to turn data Predictive Analytics into business value. But how do Business Intelligence (BI) professionals know whether they must modernize their platforms or whether their main challenges are mostly about culture, people, and processes?
"Our BI environment is only used for reporting we need big data for analytics."
"Our data warehouse takes very long to build and update we were told we can replace it with Hadoop."
These are just some of the conversations that Forrester clients initiate, believing they require a big data solution. But after a few probing questions, companies realize that they may need to upgrade their outdated BI platform, switch to a different database architecture, add extra nodes to their data warehouse (DW) servers, improve their data quality and data governance processes, or other commonsense solutions to their challenges, where new big data technologies may be one of the options, but not the only one, and sometimes not the best. Rather than incorrectly assuming that big data is the panacea for all issues associated with poorly architected and deployed BI environments, BI pros should follow the guidelines in theForrester recent report to decide whether their BI environment needs a healthy dose of upgrades and process improvements or whether it requires different big data technologies. Here are some of the findings and recommendations from the full research report:
1) Hadoop won't solve your cultural challenges