How do you want to view the data in your business

Choosing the right analytics tool

Enterprises are dealing with vast amounts of data about their customers, prospects, internal business processes, suppliers, partners and competitors. To transform this data into actionable information that can help increase revenue, profitability and business efficiency, many organizations are turning to BI analytics tools. Although the BI tools market might be considered mature, it's constantly evolving to address the changing analytics needs of today's organizations.

Analytics like anything else is about finding the right tool for the right job. We work with multiple vendors such as Azure, Tableau, Salesforce, PowerBI and many others when assessing analytics tools to support your business goals. The proper platform and system should never be done in haste or at the suggestion of just one person or report. Is it appropriate to pick a restaurant based on one online review? Perhaps. But optimizing your business with analytics deserves more consideration than that.

Analytics tools are used by both IT and business users, address reflective and predictive tasks, function on-premises and in the cloud, and can be simple to implement or require third-party integration. There are analytics tools for all jobs and all sizes of organizations. And while some will try to sway your opinion with just one industry review, don't be fooled says Gartner analyst Cindi Howson. The right tool is out there for you and OsScopo can help you in choosing the right one.

Here are three key things that managers should consider when choosing the perfect analytics tool for their needs:

Consider a tool’s current competence and capability:
Does past performance indicate a future return on investment? We verify that the tool has the capacity to handle your business intelligence tasks now, and has the capacity to let you collaborate on future projects.

Study a vendor’s completeness of vision:
Look for an analytics tool that encompasses all of the nuances of a roadmap but is firmly supported in its customer support and has developer support and connects to thousands of data sources.

A tool is more than just its ranking:
Vendors may try to sell you a tool, even a good one, just because they have it in stock and not because it’s the right tool for you. But they do provide as many options as possible for customers who need to work on a specific project or must tackle multiple projects. Analytics tools should fit the project, not the other way around.

BI analytics tool selection and evaluation criteria

Overview
Although industry analyst product reviews can be a good source of introductory research, particularly if you aren't familiar with the overall market, these reviews are often oriented toward selecting the product with the most features. Your organization should instead select the BI analytics tool that's the best fit for its use cases, meets its budget and can be implemented given its resources and skills. To simplify the process, you may wish to classify the features and functions to consider as must-haves, nice-to-haves and will-not-use:
Must-haves. This classification should be unambiguous. In other words, if the product doesn't have this particular feature, it's eliminated from further consideration.
Nice-to-haves. Although nice-to-have features aren't required, they're often the differentiators in selecting a product.

The must-haves
The following are often must-have features for organizations:

Data sources. Access to various databases and file types such as comma-separated values file, text, Excel and XML are basic staples of all BI products. Increasingly, BI analytics tools are providing access to specific applications such as Salesforce or NoSQL databases. Your specific needs will determine if these features are must-haves.
Data filters and drill-down. The product should enable the contents in a tabular report or visualization to be filtered by data values. Filtering is provided by features such as pull-down lists, search filters and slicers. The product should also allow the user to drill-down from summarized to more detailed data and then drill up.
Web-based client user interface. The product's client user interface for the BI consumer-role should be Web-based. This has become an industry best practice.
Independent and interconnected mash-ups. When the BI style enables multiple visualizations, including tabular reports, to be displayed on a single screen, the software should allow for these to be either independent of each other or interconnected.
Visualizations. The BI analytics tool must provide various chart types, as well as allow for combinations.
Security. All BI products must require both user and user role-based security.
Microsoft Office Data Exchange. The product must be able to import and export data with Microsoft Office products, especially Microsoft Excel.
Print and export. The product must allow for print visualizations and tabular reports to be exported to PDF or other graphics.

Must have features specific to self-service BI use cases
There are several must-have features that are specific to self-service BI use cases:

Select data for analysis. The BI analytics tool must enable the user to select the data used in analysis and present it as a pivot table-style interface.
Data blending. The product must permit the user to blend data from various data sources.
Create measures. The product must enable the user to create and save measures or calculations for use in analysis.
Create hierarchies. The product must allow the user to create dimensional hierarchies.
Save queries and analysis. The product should enable the BI user to save data filters, selections, and drill-down paths used in an analysis.

The nice-to-haves
These features often are the criteria that become the differentiators in selecting BI products:

Create and publish by business users. The product enables the user to save and share their analysis with others.
Context-based filters. Filters will list only choices that have values given the current selection of facts and dimensions.
Context-based visualizations. Only visualizations or chart types that are relevant to the data selected will be listed as options.
Advanced visualizations. More advanced visualizations include heat maps, scatterplots, bubble charts, histograms, and geospatial mapping.
Collaboration and social interaction. The BI analytics tool enables a business community that can share and discuss their analysis.
Storyboarding. This enables a series of reports or visualizations to be tied together in a workflow.
Microsoft Office real-time integration. The product should provide real-time integration with Microsoft Office products.
Mobile version. The tool should differentiate between viewing applications on a Web browser on mobile versus a mobile BI application.
In-memory analytics. The product should pull data into a locally cached data store.
Offline updates. The tool should allow users to schedule automatic data updates.
Performance monitoring. BI products that monitor report and data usage enable a BI group to improve analytical performance.

BI platform administration. Although all BI tools should provide code and version management, there are many application development features useful for larger BI deployments.

Other considerations
Establishing the scope of your BI project in terms of how many people will use it and what data will need to be accessed is the foundation for creating the selection criteria. Monetary considerations such as anticipated budgets are also key factors.

Analytics not just for historical analysis

Analysis of historical data has been the staple of traditional business analytics, whereas predictive analytics takes it a step further, analyzing historical and current data to make predictions about future events. At OsScopo we specialize in implementing this type of technology, for example OTBI (Oracle transactional business intelligence) can view historical, transactional and predictive views of your data.

Why choose OsScopo for your Data Analytics?

At OsScopo we work with you to understand your data and analyze your analytics needs. Based on those needs we can recommend the best analytics tools for your business.

We leverage years of experience and proven best practices to help you plan, design, implement, and support an optimized data analytics solution.

What are the benefits?

Traceable, Secure, Efficient and Visible

Long-term ROI

An analytics solution, adaptable to long-term goals.

Visible insights

Improve efficiency in anticipation of business opportunities.

Competitive advantage

Improve practices and processes to outshine the competition.

Cost reduction

Locate the problematic areas of your business.