BI to Data Analytics

Business intelligence (BI) is a mainstay of modern business. Since the widespread introduction of computers into the back office, organisations have collected information and devised ways to mine it, report from it and extract some form of value from it.

We are in the middle of a major transformation in global business, as organisations are evolving their existing BI technologies and strategies into a data analytics-based approach. This is more evolved than BI, being a process of inspecting, cleaning, transforming, and modelling business data to discover useful information, inform conclusions, fuel predictions and support decision-making. It is also a major driver of the move towards automation and artificial intelligence in the workplace, as more businesses place data-centricity at the heart of their operations.

1/3: Moving the enterprise to data analytics

The journey organisations are taking to migrate from business intelligence to data analytics

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2/3: The transformation of the data-centric enterprise

The importance of becoming data-centric in every aspect of the organisation

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3/3: The impact of artificial intelligence and machine learning on data strategy

The impact of artificial intelligence and machine learning on data strategy

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1/3 – Moving the enterprise to data analytics

The expansion of data as the driving force within business has led to both an explosion in the volume of data collected and used by organisations, as well as an explosion in the number of repositories holding it.

Fragmentation of data sources not only reduces the asset value of data, it increases the complexity of mining and manipulating that data, as well as hampering its use to drive a variety of data-centric business services. Coupled with many other challenges including confusion over leadership ownership of data strategy and a lack of data visibility, these factors make data-driven business transformation difficult, but extremely necessary for organisations to accomplish.

Using in-depth analysis of answers from IT and business decision makers in the UK and Germany, this white paper examines how and why organisations across two major European markets are making the change from business intelligence to data analytics in order to make better use of their data, power modernisation efforts and service organisational demand. It will help you to fully understand the variances in perception and actions between these two pivotal, but often differently motivated, decision-maker groups and provide insights you can use in planning, refining and delivering your own data-driven business transformation.

Moving the enterprise to data analytics

Watch this video to learn how business intelligence has been a major part of IT and data strategy, but how times are changing.

If anyone asked you to do a complete audit of all of your organisation’s data, you’d probably break out in a cold sweat. And for good reason – trying to keep track of data has become a mammoth task – especially with the falling costs of storage and the demand for data-hungry digital technologies like the Internet of Things.

Learn more about how to avoid falling into the data blackhole in our blog article!

2/3 – The transformation of the data-centric enterprise

Most businesses cannot function without data. A system failure or an outage would be a nightmare, as it sets back operations, harms the reputation and consequently profits. Unfortunately, a lot of enterprises fail to recognize the importance of data in their day-to-day decision-making. The key to a successful organisational shift is an understanding of the value of data and the benefits that a rounded data strategy can deliver.

Over a quarter of businesses in the UK and in Germany are already actively implementing a strategy to be more data-centric as they realized that data insights can deliver a competitive edge, anticipate demand, and overcome market and operational challenges. However, if data is not used strategically, it simply occupies space and costs time and money without creating value for the organisation. Getting the right tools, skills, and data-centric mentality is the way to shift from reactive to proactive decision-making.

To what extent is data understood and used within organisations?

This is the main question examined within this white paper by looking at two major European markets. The key aspects of this study are the following:

  • What are the companies’ processes of becoming more data-centric in their day-to-day operations?
  • Who owns the data strategy within the organisations and how does that compare with who uses data the most?
  • How critical is the availability of data sources to everyday business activities and operations?
  • Are organisations extracting all the value they expect from their data?

Making the Enterprise Data-Centric

Watch this video to learn how to move towards data-centricity and why is it important for success.

3/3 – The impact of artificial intelligence and machine learning on data strategy

The white paper is coming on September 26!

In this third whitepaper, we examine how every aspect of the business world is being disrupted by artificial intelligence (AI) and machine learning (ML) right now.

Everything from supply chain and stock control to the automation of factories and repetitive data entry tasks is leveraging either AI or ML, with a ready supply of clean, accurate and detailed data essential to drive these algorithms. The need to service automation and cognitive systems is shaping data strategy business-wide as companies try to get their data assets in good order to support AI and ML business aims.

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