NEWS

Where to start your data-driven journey

Looking for value in all the right places.

At a recent visit to a local bookstore, I noticed something I hadn’t spotted before: there were far more books on self-help than there were on the subject of business improvement. At home, I did a quick search on Amazon.com: more than 100,000 books on self-help, only 30,000 on business improvement. It made me think: based on this, it’s quite a bit easier for us as individuals to get guidance when we want to improve. You basically ask yourself the question “what is it that I can’t do today that I wish I could?” and, hey presto, there’s a book to show you the way.

When companies ask themselves such questions, the answer often comes back pointing to digital transformation and the need to become a data-driven organisation. But with only 611 books on the subject of ‘data-driven business’, it’s obvious the guidance on that subject is a lot thinner on the ground than if I’d like to ‘lose weight’ (20,000 books). While I very well know where to start shedding the pounds, how do you even get started as a business to become more data-driven?

It’s a journey

Becoming a data-driven organisation is not a binary affair, it’s a journey in three stages. It’s easy to feel despondent when you read how others achieve really amazing and perhaps slightly esoteric transformative business use cases. Those organisations did not start there and you’re seeing one of the end (or perhaps even intermediary) results, definitely not the first step.

The most common first step is all about visibility. You are simply trying to report better on the data that you already have; making it more visible, more apparent, easier for executives to understand and make decisions from. With that in place, you can graduate to the next step: productivity. Now you empower more people to get access to the data and analytics directly. So, rather than having to ask IT for data, your employees can access information independently (but still secure and governed) through their tool of choice, in their own right. It is this productivity that now paves the way for the transformative business cases, those that are strategic in value and have tremendous applicability to a core part of a business.

Five steps to success

Although technology plays a part in becoming a data-drive organisation, people and process also have a big role. Thankfully, we’ve guided many of our customers through this and are well aware of the steps they must take in order to complete the three-step journey successfully. The first step is to build a data-driven culture. This means that all of your decision-making really needs to be based on data and not just gut instinct. Second, you need to develop the right set of skills and the right team to analyze your data. Then, you need to think in an iterative fashion, become agile and lean in your development process. Fourth, the data engineering and devops teams need to start working hand in hand with your data scientists in order to make the process work at scale and in production. And then lastly, you need to think about right sizing data governance. Everything that you do needs to be something that you can trace back, understand the lineage of, and be fully compliant around.

Usual subjects

Although data-driven insight can help all parts of an organisation, there are some use cases that stand out as well proven, high-value projects, when data-driven insight is applied:

  1. Detecting cybersecurity threats – the volume of data that allow organisations to do this at scale is tremendous: content, logs, relationships between people or systems, and patterns of activity. The bigger the history, the better the chances of finding fraudulent behaviour or criminal activity. Sophisticated detection, analysis, and prevention algorithms based on complex models from historical data let organisations monitor real-time activity. Companies can better analyze and prevent cybersecurity threats efficiently and effectively.
  2. Reducing customer churn – data analysis is key to determining customer preference and building customer lifetime value. However, to successfully analyze complex problems like customer churn, data from many sources is required. By combining these data sources, it’s possible to create models that tie together market forces, customer preferences, and company operations into a holistic view of customer retention that can positively impact profitability and company performance.
  3. Targeting advertising – a wide variety of source systems must come together to enable this: content, user activity logs, relationships between people or systems, and patterns of activity. To do it right, you need to be able to store and quickly analyze new data sources as they become available. Through analysis, organisations can understand user behavior, create targeted ads using advanced analytics, and apply machine learning to optimize ad yields. You can then better analyze ad effectiveness and maximize revenue to both the ad owner and the advertising network.
  4. Delivering search results – online search is a problem of massive data sets, rapid analysis, and meaningful results. Storing and analysing near unlimited amounts of data, provide results that take into account user behavior, preference and history, and match query results to user needs. For businesses like online retailers, accurate and meaningful search results drive profitability and customer retention – helping build engaged and satisfied customers.
  5. Predicting outages – monitoring key system parameters real-time and analysing it in context let organisations move from a reactive approach to outages to one that is more predictive in nature. The impact is one that goes beyond improved customer satisfaction and reputation (no one likes the plane’s engine to fail just when setting off to your favourite holiday destination); there are further savings to be made by being able to schedule resources to be available at the right place and the right time.

If Cloudera wrote books, we’d definitely contribute to the ‘business improvement’ section, helping companies answer the question of “what is it that I can’t do today that I wish I could and for which data and insight are key?” Besides a modern data platform that enables the journey, we also provide the services and support to bring it to a good end. Get in touch to start planning your journey.

 

Article by Wim Stoop, Senior Product Marketing Manager, Cloudera

Wim Stoop is the senior product marketing manager for Cloudera. In this role, he leads the marketing direction and strategic vision for Cloudera’s mission to let organisations turn data into business value at scale. Prior to Cloudera, Wim spent more than 17 years helping blue-chip companies such as IBM, BP, and HSBC solve their most data-intensive challenges in the context of their business objectives and usage scenarios. Wim is a regular speaker at industry events where organisations are deciding and defining their big data strategy and direction. Wim holds a degree in Chemical Process Technology from the Eindhoven University of Technology in The Netherlands.

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