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This eBook outlines and compares five different big data approaches which you can draw upon to build a forward-thinking and innovative strategy. Each approach is currently used by the few companies currently leading the way in this exciting new field.

Chatbots and voice recognition technologies provide opportunities to deliver far more than an additional way of communicating with employees and customers. This eBook provides an overview of the tools, technologies, and approaches being used to drive greater customer engagement across both front and back office functions.

Trevin Erichsen, Manager of Analytics and Insights at Sunsuper explores the challenges associated with effective data management and delves into how building the right culture and the right governance frameworks is helping mitigate risks and allowing Sunsuper to effectively harness data in business operations.

Data is increasingly considered to be the greatest business asset and there is more and more attention paid to an organisation’s data management strategy. Organisations can achieve useable, valuable data by having excellent approaches to data acquisition, storage, governance, analysis and security. However the next step is for the organisation to use that data to create new revenue streams – to monetise the information.

Here we look at seven specific strategies that you can apply within your organisation to monetise your data.

In this paper BDO seeks to demonstrate how building a mature information security and data privacy programme can enhance the professionalism of a company's employees and reinforce an organisation's public reputation. It explores the intrinsic value and hidden benefits organisations can achieve through meeting and exceeding their data protection obligations.

For many CDOs their initial work has focused on creating a data culture, gaining bu-in, overcoming silos, and unpicking the challenges of legacy systems, data spaghetti, and crucially, governance. With those first phases now settling down, we can look to predictions for the next stages and ask, what are the actions and outcomes that we can expect to see next.

This year will be a turning point for many organizations as they realize that just being “data driven” doesn’t guarantee future success. The future belongs to the enterprises that anticipate constantly evolving regulatory, technological, market, and competitive challenges, and turns them into opportunity and profit. It belongs to enterprises that are able to connect to any data and distribute reports to thousands. It belongs to the enterprises that go beyond business intelligence to deliver insights to every department, device, and constituent through natural and zero-click, realtime experiences.

It belongs to the fully realized Intelligent Enterprise.

Executives are responsible for making decisions that can make or break a company. Yet, they have little time to dig through and make sense of data sitting in spreadsheets and databases. To lead well, they need to be able to keep both the big picture and the details of day-to-day operations in mind. They need tools that can give them quick, easy, and secure access to accurate, up-to-date information on business performance so they can make more informed decisions that positively impact their organization. 

MicroStrategy's advanced analytics and mobile capabilities allow executives to securely monitor critical information related to finances, sales and marketing effectiveness, and employee productivity, empowering them to ​develop data-driven strategies that drive growth. 

As a result of the global financial crisis, financial services institutions have come under greater scrutiny, and the environment in which they operate is increasingly characterized by unprecedented economic, regulatory, and technological change. Now, more than ever, decision makers need to be sure that their technology investments will pay off—choosing the right business intelligence (BI) solution is no exception.

Click through to dowload and find out what you need to consider before selecting the right BI solution for you.

Artificial Intelligence is expected to permanently change the banking industry in profound ways during the coming months and years. Companies want to seek a competitive edge by implementing more technology to achieve improvements in speed, cost, accuracy and efficiency. 

As enterprises become more complex, and success increasingly depends on streamlining operations, it becomes imperative to invest in emerging technologies that enhance efficiency and facilitate improved decision-making in the back-office. Robotics Process Automation (RPA) brings you one step closer to this goal by significantly reducing turnaround time, interacting with multiple applications in a non-intrusive manner, and enhancing accuracy and reliability. With its ability to stitch an automation story across multiple application environments, it streamlines your back-office operations, making it possible to realign your value proposition to meet changing customer expectations and thrive in a dynamic business environment.

Digital transformation trends have resulted in a data explosion across industries. Enterprises are increasingly leveraging Artificial Intelligence (AI) and Machine Learning (ML) to identify trends, harness insights based on data, and make critical business decisions to gain a competitive advantage in the market. This paper explores the key trends and insights in advanced machine learning.

In this white paper, you will gain understanding of the simple steps required to build a business case for IA, including the benefits of using a Business Case Tool to quickly and easily model many processes, understand the potential savings and prioritise accordingly in order to build momentum and maximise automation value.

Chief Data Officers (CDOs) can drive data strategy, support machine learning analysis, and generate business value with data. We live in a world rife with rich data and open-source tool support. However, there are many obstacles between CDOs - or any data leader - and successful organizational integration of data insights (lack of executive buy-in, shortages of data scientists, and dated, disorganized data, to name a few). We wanted to explore the intricacies of the role and uncover the path to data leader success. Dataiku collaborated with Caroline Carruthers, of Carruthers and Jackson, a CDO who literally wrote the book on it, (The Chief Data Officer Playbook, Facet, 2017) to provide new datasets and insights into ways to ensure CDO success.

This white paper includes:

• An expose into the different types of CDOs and what kind of support and knowledge each needs to succeed;
  
• Insights from more than 50 top cross-industry CDOs on the challenges they’ve faced and the solutions they’ve driven in their organizations;
• Context on the Data Revolution and tips on how organizations can drive it forward; and
• Exploration into the future of the data leader community and insights into why joining is beneficial.
  

You are the CXO of a company that serves as a sales platform for thousands of different clients. You and your management team have identified a list of processes that could be improved via better use of your data and advanced analytics. For instance, in order to help your clients increase sales (and thus increase the stickiness of the platform), you decide that the development team should surface a custom recommendation module offering three product recommendations per client.
Requirements include that:

• The recommendations be available in real time and
•  The recommendation engine can be updated without causing platform downtime

At the same time, there are internal requests from different teams (like sales and marketing) who want to make data-driven decisions (for example, key trending products with positive reviews from social networks or how transformation rates are influenced by the historical browsing behavior of a visitor), but their old dashboards are static and don’t address their needs. Even though the data exists internally, they can’t get insights for themselves because they don’t have direct, regular, monitored access to data that can help them do their jobs.

Which need should be prioritized? And how do you even begin to tackle these projects with an approach that will be sustainable and reproducible for other projects and requests down the road?

There is a revolution happening in analytics and that is the move towards self-service. TDWI research indicates strong interest in self-service business intelligence (BI), analytics, and data preparation solutions. For instance, as far back as 2013, close to 80 percent of respondents in a TDWI survey said it is important to implement analytics solutions that do not require significant IT involvement. Companies are still very interested in this today. Self-service analytics technologies are an important trend for democratizing BI and analytics, which is about giving more users better tools for interacting with and analyzing data. Companies want to evolve their analytics strategies beyond spreadsheets or simple dashboards; many seek to build a broad “analytics culture” in which analysis plays an important role in decisions and is fundamental to business collaboration.