Top five trends for harnessing data in 2019

Harnessing data 1: Data storytelling is the new language of organisations

It’s now a critical skill for analysts to be able to convey the steps in their analysis that led to insights in an actionable, easy-to-understand way. This is “data storytelling.” However, we’ll see the definition of data storytelling evolve greatly in 2019 as organisations create a richer culture of analytics. Instead of presenting a singular conclusion, data storytelling methods will be about encouraging a wider conversation about what the data insights are. This puts responsibility on both the dashboard creator and the audience with their diverse perspective to come to a conclusion around what the data tells them. Embracing data storytelling across roles will amplify the potential for business impact as data is used to more exhaustively to engage, inform, and test ideas organisation-wide.

Unreliable storytelling is a fact of life, so how can we get to the truth in data analytics?

Even when trying our best to be reliable narrators, the most honest storytellers can’t always be trusted

Harnessing data 2: Data curation converges with modern business intelligence platforms

With greater diversity and complexity of data sources, and more of the workforce using data to drive decisions, data management is more critical than ever. Companies will increasingly use data curation—which includes capturing, cleaning, defining, and aligning disparate data—to bridge the gap between data and its real-world applications. Data curation tools and processes (like data catalogues and semantic governance) will be merged with BI platforms to link data with its business context and maintain governance at scale. This will help everyone verify the origins of the data origins. Ultimately, governed data curation will provide a stronger foundation for the entire analytical pipeline, helping users to move beyond asking questions of their data to asking questions of their business.

Artificial intelligence: Data will be the differentiator in the marketplace

Kicking off Information Age’s Artificial Intelligence Month, we look at the importance of data in the future adoption of AI; with the help of Greg Hanson, CTO & VP at Informatica

Harnessing data 3: New Data Commonwealths amplify social good impact

 The “data for good” movement is exploding as non-governmental organisations (NGOs) and non-profits realise the benefits of using data in social impact initiatives. In fact, Gartner research shared that “social media mentions of data for good have increased 68 per cent in the last year” as the public realises how data can positively impact society.

Previously, these organisations didn’t have resources to invest in a sophisticated data infrastructure or dedicated teams of data workers. That has changed. With the cost-efficiency and flexibility of cloud computing, NGOs and non-profits can now develop sophisticated data environments, without massive on-premise investments.

What will become more prominent in 2019 is how NGOs and non-profits create data commonwealths, which are platforms for data sharing and collaborating across organisations to achieve a goal. They will drive the conversation around the factors that build trust within these partnerships, including the responsible use of data. While collaborative projects don’t come without challenges, the continuing growth of the “data for good” movement in 2019 will reflect the altruistic potential of sharing data to solve our most difficult global problems.

Artificial intelligence: Data will be the differentiator in the marketplace

Kicking off Information Age’s Artificial Intelligence Month, we look at the importance of data in the future adoption of AI; with the help of Greg Hanson, CTO & VP at Informatica

Harnessing data 4: Codes of ethics catch up for data

Data regulations like GDPR are making leaders assess the future of ethical data practices within their organisations. Data privacy isn’t going away anytime soon for consumers, either. 2019 will see further movement to create, strengthen and apply new codes of data ethics. Many professions like the law and medicine are bound to a code of ethics.  With the sensitivities around data proliferation, more companies will be evaluating how to apply these same principles to their data analytics practices. If they haven’t already, Chief Data Officers (CDOs) will be helping to draw up these codes of ethics to frame future infrastructure, governance, and staffing decisions.

MPs outline plans for Centre for Data Ethics and Innovation

This afternoon MPs updated Parliament on plans for a world-first Centre for Data Ethics and Innovation

Harnessing data 5: Data democracy votes for citizen data scientists on artificial intelligence and data independence

Whose data is it anyway? talks about idataty, the democratisation of data and his optimism surrounding artificial intelligence

Instead of simply handing over their results, data scientists will increasingly participate in how results are applied to the business. This means they will need to have better presentation and visualisation skills to communicate their findings to leadership and to collaborate with other people in the organisation working with data. What’s changing for data scientists is how they will be working alongside a fast -growing cadre of citizen data scientists. These are people whose primary job function is outside the field of statistics, but who generate models to develop and test hypotheses almost every day. Self-service analytics tools will help these roles collaborate, explore and better understand data to create insights that seriously impact the business.

James Eiloart is SVP of EMEA at Tableau

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Michael Baxter

.Michael Baxter is a tech, economic and investment journalist. He has written four books, including iDisrupted and Living in the age of the jerk. He is the editor of and the host of the ESG...

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