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The Little Book of Business Intelligence

Business intelligence systems were first introduced into organisations in the 1960s. These early systems would be recognisable today but were limited in scope, acting to support decision making by bringing automation and MI into the equation. From these early days, the products on the market have evolved and the market has grown extremely fast.

Today, more than one hundred BI delivery firms sell at least one type of Business Intelligence software. For buyers, the pace of change in the marketplace, the growing possibilities and power from these systems, and the ever evolving landscape of business and its needs means that it can be a complex proposition to match management needs with the right tool. We have produced this guide to help you to understand today’s tools and the marketplace, and to put your own needs into context.

The guide is divided into the following sections:

• An introduction to BI software

• A guide to selecting the right BI tool for your needs

• Other data management solutions

• Applications for Data Discovery

• Available reporting tools

• Understanding your buyer ‘type’

• Recognising key market trends

• Latest developments in the marketplace


An Introduction to BI Software

Business Intelligence software - BI for short - helps organisations to make sense of the enormous volumes of data they need to process to function effectively. It helps those organisations to structure and to read that data in an objective, results-focused way that is reliable, auditable, focused - and which ultimately aids decision making. The systems deal with a range of data sources, from internal departmental data, to external and bought-in source data, such as marketing analytics, social media usage demographics and even macroeconomic indicators.

The market for this type of data is soaring because organisations are dealing with ever greater volumes of data, and struggling to analyse it in a reliable and meaningful way. Those firms which have invested in tools and applications such as Customer Relationship Management (CRM) and Enterprise Resource Planning (ERP) now own vast reserves of data that requires analysis in order to use it to drive better and more accurate decision making. At the same time, the exponential growth of digital means that business customers increasingly need and want tools that can handle these huge data sets and analyse them without human intervention.

One notable trend in this market has been a move towards increasingly user-friendly software design and architecture, so that the resulting application doesn’t require the business user to have a specialist degree in programming. ‘Friendly’ systems are also helping to drive forward adoption and demand, meaning that a broad range of business users - not just IT staff - are keen to access data sets across internal and external sources in a bid to make better management decisions.


A guide to selecting the right BI tool for your organisation

Business Intelligence software broadly falls into three categories of application: tools for data management, applications for data discovery, and tools to aid reporting. These include specialist data visualisation software such as infographic production, and dashboard data provision for ease of reading. We’ll now look at how these different tools and applications can help your organisation to become more robust and data-driven in its decision making.

The type of BI tools your business or organisation will ultimately need will depend largely upon your analysis requirements and your current data management processes and capabilities. For example, if you have a range of disparate data sets scattered across databases that aren’t linked in any way, you may need to start by commissioning a centralised data warehouse, and then invest in tools that allow you to extract, transform and load data. These are known as ETL data management tools, and they help you to rapidly organise and structure data in a way that matches your particular and immediate search need.

Once your data has a common format and structure, you can look at solutions for ‘data discovery’, text mining, data mining and semantic mining. These allow you to create your own reports on an ad-hoc basis, and you’ll hear terms such as Online Analytical Processing (OLAP) bandied around at this stage. Essentially, because your data will be stored safely within a central warehouse, any user will be able to create a custom report without affecting software applications such as ERP, CRM or supply chain management and logistics software.


Other data management solutions

However, there is more than one way to approach this and more than one way to successfully implement Business Intelligence within your organisation. A data warehouse and ETL isn’t necessary if you only need to analyse single-source data. At the other end of the scale, your needs may be so complex that your business requires several data warehouses, and a range of connecting tools to link servers, applications and the data itself.

Ultimately, improved decision making is only possible if the underlying data is of the right quality. Your organisation will use data management tools to clean any inaccurate data and to organise the resulting datasets in a useful way by providing user-guided structure and format via databases. There are solutions and providers that help businesses to keep their data clean, free from errors, and structured in a standard way that aids reporting.


Applications for Data Discovery

One of the greatest benefits of investing in BI tools is gaining the ability to rapidly sift through huge volumes of data, extract the insights you need, and use these to draw confident and meaningful conclusions. This is helped via a subset of data discovery applications. These help users to understand the data they are reading through complex computations, advanced algorithms or during OLAP.

Data mining applications automatically sort through data sets to seek out unknown or new patterns. This tends to be a fundamental step that other processes, including predictive analytics, will later rely upon. The tools are needed because large databases are too tricky for people to assess for patterns. The data mining tool will help the user to find key areas for further analysis by looking for trends that are yet to be explored.

OLAP (Online Analytical Processing) helps the user to rapidly analyse a range of data across dimensions and perspectives. It will consolidate data, sort it and classify it, analysing the resulting data from different perspectives such as volume of sales for a certain product set, across a particular retail geography and for a certain month.

Predictive analytics are subsequently employed to make data-driven predictions about forthcoming opportunities and risks alike. Credit scoring works in this way, using the applicant’s current financial status to make predictions as to how they are likely to behave with credit in the future.

Finally, there are text and semantic analytics tools which assess text in large volumes to look for sentiment, relationships and patterns. Social media is a key target for these, and companies use the tools to find out if their customers are satisfied with their service or engaged with their brand, amongst other things.


Available reporting tools

Reporting tools allow the user to see things they might otherwise have missed. And this of course is the real beauty of these BI systems. The user is increasingly coming from the business rather than the IT team, and they want to be able to access information in a way that is fast and simple to understand, as well as being instantly customisable. Software developers have been working hard in response to make these highly complex BI applications appear to be simple to the end user.

They do this by focusing on the way in which reports can be presented back to the user. For example, this can be via graphical visualisations instead of numbers or text, ready to insert into a dashboard or presentation. Increasingly, these visual reports can also be interrogated in real time, which is a great asset in a business meeting as ideas are being thrown around the room.

Dashboard presentation allows the users to see KPIs that are customised to their particular needs. And because the reports are usually delivered via a browser, anyone with the right permission can access them at any time.

There are also report writers which let the user choose the design and structure of their report, which can be based upon custom and complex queries. This is a significant benefit for organisations which regularly adjust their analysis needs and rapidly need new reports as a result. There are also scorecard options, which essentially take dashboards up a notch and help users to assess progress against key metrics.


Understanding your buyer ‘type’

Any business buyer needs to know what category they fall into before looking for the right BI solution. There are both department and business user buyers, who will typically be best suited to a smaller and data-discovery based solution, rather than substantial, traditional business intelligence systems. The key factors for these users will typically be speed of use and ease of use. These take precedence over integration and in-depth, complex user functionality. These users are typically based in the business itself, rather than in an IT department.

The second group is IT buyers. These are the traditional consumer of business intelligence technology and are more interested in IT infrastructure integration and functionality, rather than the attractiveness of the reports or ease of use. Integration, specification and technical capability are the key drivers for this user group, and software vendors will tailor their product offering accordingly.


Recognising key market trends

There are two primary trends which are well worth knowing about. The first is about in-memory processing. Older OLAP systems used pre-calculations to assess data combinations and these were stored safely in ‘the cube’ for extraction and analysis. The creation of these storage cubes took a long time and required specialist expertise. However, today’s software and hardware capabilities are more powerful, cheaper and faster, allowing analytics to process in real time.

The other major trend is known as “big data.” Today’s digital world is generating vast quantities of data which requires analytics software providers to enhance their analytics capabilities and warehousing in order to meet rising demand. The majority of businesses cannot yet exploit their big data to gain that all-important competitive advantage, and the next generation of BI tools will be needed to do this.

Those companies dealing with huge data sets are also considering their IT security - or should be doing so - as a priority.

Another interesting trend is the increase of business users relative to IT staff. Nowadays, business users are starting to buy software directly, and usability becomes an overriding feature, rather than functionality. This gives smaller data vendors a real opportunity if they can develop fantastic visualisation software.

Two other notable trends are SaaS (software as a service), which is cloud-based for a lower cost BI solution, with faster implementation times and reduced need for specialist IT resource to support; and mobile BI applications, which can be accessed by phone, tablet and on the go.


Latest developments in the marketplace

There are some new developments which are worth knowing about in the BI field. Last April for example, Microsoft bought out Datazen, the mobile BI platform. This will allow Microsoft to make its Power BI offer function better on phones, and should open up the market to new customers too.

Additionally, Birst, the cloud-based provider of BI solutions, managed to raise an impressive $65 million in venture funding as it prepares for an IPO. However, fortunes are rather more mixed for Hadoop, the open-source program used for dataset storage and processing of big data. In a survey, just over a quarter of software developers said that they were experimenting with the platform or were currently deploying it.

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