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SmartData Collective > Uncategorized > Data Quality Predictions for 2015
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Data Quality Predictions for 2015

martindoyle
martindoyle
8 Min Read
Data Quality Predictions for 2015
Illustration generated with FLUX.2 [klein 4B] via Cloudflare Workers AI.
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The champagne has been drunk, the mince pies are eaten and we’re packing away the Christmas baubles for another year.

Contents
  • New Years’ Resolutions
  • Knowing Your Customer – Perhaps Better Than They Know Themselves
  • Big Data Efficiency – and the Internet of Things
  • Maturing Social Media, or ‘Beyond Likes and Shares’
  • Facing the Challenge

The champagne has been drunk, the mince pies are eaten and we’re packing away the Christmas baubles for another year. After a well-earned rest, thousands of businesses are returning to face the challenges that the New Year will bring to their business, and that means refocusing efforts on quality, usable data.

But the world of IT rarely stands still, and 2015 will bring immense change that will intensify our use of data and change our dependence on it.

New Years’ Resolutions

Many of us put a few projects to one side last December, pledging to deal with them after the festive break. If you brushed your dirty data under the carpet before shutting shop, January is a good time to bring it out into the open for a spring clean.

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But before you begin, think about the way your use of data will change. Each year sees advancement in data and technology. This year, we’re looking at some big changes that will force businesses to broaden their scope and scale up their data quality assessments.

Knowing Your Customer – Perhaps Better Than They Know Themselves

Google is keen to use customer data to provide more intelligent results. Rather than simply searching for answers, Google wants to tell us what we need before we actually need it. If you have used Google Now, you might have noticed that Google knows where you are and gives you your best route home automatically. It also tries to predict what you’ll want to read when to get there.

In order to make these kinds of predictions, Google needs very high quality data. It sifts through all of our interactions to try to figure out what we’re planning. It also places ads alongside its predictions, so there’s money to be made in getting it right first time. Marketers have always been interested in consumer behaviour, but technology like Google Now will drive an increased desire for accurate and usable data that’s always clean and accurate.

Big Data Efficiency – and the Internet of Things

Companies are always looking for new ways to harvest meaningful data about their customers. Surveys and loyalty cards are useful, and we can learn a lot by split testing ads and segmenting databases. But for huge competitive advantage, we need to look beyond our own data harvesting and seek to borrow insight from the data that’s all around us.

Collectively, the data we all generate is known as Big Data – ‘big’ because there are petabytes of it at our disposal. From Open Data repositories to the World Wide Web, we can potentially tap into tens of thousands of sources of real insights that are constantly being generated.

There’s also a new initiative for businesses – the Internet of Things, or IoT. IoT is a new concept that will see assets given their own identifiers and sensors so they become ‘aware’, independent of human monitoring.

In a modern factory, every piece of machinery – every component of a production line – will be able to continually report its status, its movements, its temperature, its position and any other relevant data types. In one building, the Internet of Things could see tens of thousands of individual sensors, all reporting tens of thousands of measurements every second.

Clearly, 2015 is leading us towards a new era of massive data production, and there is great potential when we can derive information, knowledge and wisdom from such massive datasets. But collecting huge amounts of data presents new challenges, too. How will businesses process data quickly? How will they know what to discard? And how can they keep data clean if they have more and more of it to process?

As a CEO, it’s your responsibility to drive the business forward and look for new ways to gain insight into your operations. Businesses that stick with the status quo will find themselves outpaced by businesses that brave new Big Data challenges. And businesses that embrace Big Data, or invest in the Internet of Things, will need robust data quality procedures to deal with the influx of 1s and 0s.

Otherwise, Big Data is no benefit, since disorganised and low quality data is simply expensive background noise, and the business will need to store increasing amounts of data that it cannot make any sense of.

Maturing Social Media, or ‘Beyond Likes and Shares’

Few businesses are ignorant of social media and the benefits it provides to business. Large brands have matured their social standing and monitored every single post to achieve maximum engagement with the next. Data gathered from social campaigns and interactions feeds back into the single customer view, and provides a unique insight into content marketing trends. And social data slots into wider inbound marketing objectives, something that then influences optimisation, content marketing and more.

In 2015, we’ll see aggressive optimisation of social media campaigns based on accurate data from analytics. This may include discarding some channels and focusing more on channels that are proven to be converting. This means more opportunities to optimise marketing messages, and more reasons to continually clean data coming in from social networks.

Facing the Challenge

Businesses are obtaining data in new ways, and we are moving towards a more connected world where more data is available if we want it. But quality over quantity is key. This is a central concept in our predictions for 2015: more data is great, but more quality data is better.

Security, cloud computing, archiving, location, live streaming and data intelligence will all influence businesses in the year ahead. As our systems become more intelligent and start to control their own behaviour, we’ll all need to maintain a pin-sharp focus on data quality so that all of these different advancements can benefit the way we work.

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