5
The business drivers behind BI have elevated it to one of the highest priorities of CIOs and
CTOs. To maximize their return on investment, realize the full value of BI to the business, and
enhance their business competitiveness, IT executives need keen awareness of the
challenges related to BI projects.
With respect to the IT infrastructure, we now see three major challenges:
Provide sufficient resources to run complex queries, including predictive analytics
Provide an IT infrastructure capable of running intelligent extract, transform, and load
(ETL) processes across multiple locations, databases and servers in an increasingly
timely manner
Provide an IT environment that is highly available
It is all about speed
Business intelligence is about speed, time to market, and making decisions in real-time or
near real-time.
Analytics is a recent extension to the BI solution that enables you to perform
predictive analysis by applying statistical and trends models over collected data. It is a more
sophisticated and resource-intensive usage. Driven by business requirements, BI usage has
changed its deployment methodology and has become more in-line and real-time, using
operational data instead of historical data. This new behavior demands high processing
capacity and the ability to manage priorities according to business goals.
Raw data is meaningless
Business intelligence and analytics rely on the availability of the massive amounts of data that
organizations generate every day. The BI and analytics challenge involves coping with the
amount of data dispersed all over the different parts of the organization, bringing it together to
form meaningful knowledge, extracting meaningful information, and providing this information
to the business in the right format, at the right time, and to the right individuals.
Building a BI or analytics solution requires a sequence of steps to ETL the data into a data
warehouse. These steps are usually performed by sequences of long-running batch jobs that
run at certain intervals. These solutions become even more complex if the data sources are
scattered across multiple geographies, databases, and servers with different availability
windows and differing levels of data accuracy.
BI is becoming mission-critical
As the use of BI becomes more widespread, from the IT perspective it begins to resemble
traditional transactional processing (OLTP), which makes business intelligence applications
more critical in terms of infrastructure requirements. For example, executives often have a
dashboard panel where they track business performance in real time. Depending on the
performance indicators, they may take actions and receive rapid feedback on the dashboard.
Behind that dashboard sits a set of BI applications feeding the executive interface. Such
Challenge: The main challenge in the BI area is to be able to retrieve meaningful
information from massive amounts of data, in a timely manner, and make it available to the
right individuals.
Challenge: Business intelligence and business analytics increasingly require massive
computing power.
Challenge: Populating a data warehouse from timely and accurate data scattered across
databases and servers in different geographies is a major challenge.
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