Get started Bring yourself up to speed with our introductory content.

Getting started with cloud analytics services and tools

Cloud analytics and BI are useful tools that help companies make informed, data-based business decisions. Read this tip to find out how to take advantage of those uses.

Cloud-based analytics, like business intelligence (BI) analytics, is based on data -- but the data is gathered from multiple data sources within public or private clouds. The business value of cloud analytics is the same as BI in that cloud analytics gathers real data and puts it into an understandable form that supports informed, strategic and operational decision making for businesses.

Cloud analytics services or tools are delivered through cloud models that include hosted data warehouses, SaaS systems and social media. Currently, most cloud analytics systems are SaaS- or PaaS-based solutions, but new vendors offer a hybrid cloud solution that lets BI sources incorporate public and private clouds.

Most cloud-based analytics use dashboards to display business data visually and in raw form, depending on the display choices made when the tool is configured, or on what data an organization decides it needs to see: for example, marketing results for a campaign, sales based on region or business size, client engagement or customer trends. How an organization customizes the data gathered is how it's presented. Everyone with access to the analytics can analyze the data and make informed business decisions. Cloud analytics aids in strategic planning, improving operations and standardizing business methods across geographic locations or various operation types. The data collected allows decisions to be based on facts rather than assumptions or estimated projections. The key to making accurate business decisions is defining what data is used and which parameters are used for analysis.

Planning for accurate and useful results

Before deciding on a cloud analytics service or tool, an organization needs to identify and agree on the data that will be used and displayed. A business needs to know which data it wants to see to answer specific questions, otherwise the data returned is useless. Keep in mind that although dashboard displays and graphics have improved, accessing data has not. Data warehouses tend to be slow, and gathering data from multiple resources takes significant time. Don't expect to click a button and get instantaneous updates, because the data processing function needs time to gather results, especially with more complex data queries or if a large number of cloud data sources are being accessed.

BI in the cloud is not easy to implement. Strategic planning is required to define the questions a business needs answered and the parameters used for the resulting dashboard display and analysis. Additionally, project managers need to communicate with -- and allocate -- engineering and IT resources to ensure the right data is queried and the custom configuration settings within cloud analytics services or tools are defined based on the questions. Again, having a well-communicated and thorough plan is essential for successfully collecting accurate data to use for quality analysis and business decisions.

The true value of analytics is discovering something in the data that wasn't previously known and being able to react in a timely manner.

Equally important is defining who does the analysis and how results are translated and determined. The value of cloud analytics is not only getting the answers to expected business questions, but also to find new questions or information.

Invest time in planning which data a business needs and the parameters to use for analysis. Business decisions made from cloud data analytics are only as good as the data and the analysis behind them.

Analyzing the results

Once data queries are storing data and producing visual displays in the cloud analytics dashboard, it's time for analysis. Dashboard displays for BI are human-oriented. A human has defined the data queries; a team of humans has determined what data to pull from where and now that data is displayed. Understanding and using the data is next. Business management professionals and other users can now dive into and determine the answers to the original business questions, and attempt to uncover something in the data that generates new questions or concerns. Take the time to allow users to analyze the data, compare information and generate valid results.

The quality of the analysis influences the quality of the answers and thus the business decisions made from it.

Making accurate, fact-based business decisions

Making business decisions based on real data improves decision accuracy. A business can use cloud analytics results to improve confidence in decisions made to build and drive the business forward. Daily or weekly data updates to the dashboard make business leaders aware of changes that need to be dealt with and allow others in the organization with access to the dashboard to raise questions or provide input.

When leaders and others are given access to dashboard data, there is more creativity and input on questions the data raises, outside of the ones originally planned for and predicted. The true value of analytics is discovering something in the data that wasn't previously known and being able to react in a timely manner.

Plan the time to customize the cloud analytics displays so viewers get the information in a way they can understand and analyze it. Just displaying data is not as useful as displaying intelligent, defined data in a manner anyone accessing it within the business can accurately analyze.

Cloud analytics and BI are useful tools that provide data for informed, data-based business decisions. New ideas and ways of expanding the business or making it better come from analysis of real data. Data is meant to inform and inspire; a business can use data to its advantage by using a cloud analytics services or toolsets.

Next Steps

The rollout of Wave, the Analytics Cloud, brings questions

Trends in business intelligence and analytics

Glossary of business intelligence and business analytics terms

Dig Deeper on Big data, machine learning and AI

Join the conversation

1 comment

Send me notifications when other members comment.

Please create a username to comment.

Have you run into any problems when trying to use cloud analytics? If so, what were they?