As 2020 comes to an end, let’s take a look at how the data environment has changed and where we expect trends to head next.

We all know 2020 was a year unlike any other. As we face an economic downturn, more businesses continue to close for good, employees are being let go from their steady jobs, and unemployment claims are on the rise. 

The world of data was already changing rapidly. Big data has made processes much more complicated but also opened up access to information like never before. Advances in automation, software, and data collection techniques have also altered the landscape. And with the pandemic still present as we leave 2020, there are many changes still to come.

In this article, we’ll look at the most important data considerations coming out of 2020, including:

  • COVID-19 and spending
  • AI to improve data quality
  • Organizational efficiency
  • Data privacy

COVID-19 may impact data spending

According to the IAB report, The State of Data 2020, third-party data spending was up 6.1% in 2019. And, spending on data management, processing, and integration also grew by 9.8% in 2019, reaching $5.5 billion.

However, the effects of the COVID-19 pandemic may have causes decreases as the year progressed. The report predicted that the coronavirus would contribute to data cuts of 10% to 20%, relative to original budgets, in Q2 and Q3 of 2020. We don’t have those actual numbers in yet, there was likely a decrease in data spending through at least the middle of 2020. 

If data spending follows trends similar to consumer and business technology spending, those declines are likely past us. Across the economy, 2021 spending is predicted to return to pre-pandemic levels. A recent Trust Radius report, for example, found that most businesses expect 2021 technology spending to equal or exceed pre-pandemic levels, and only 17% expect it to decrease.

Using AI for better data quality

Data quality is frequently on the minds of marketers and analysts. Without accurate data, efforts to reach consumers and audiences can easily fail, wasting precious time and money for companies across industries. Data quality issues include inconsistent, outdated, inaccurate, or incomplete data, which can become commonplace when many different data sources are used.

One solution is artificial intelligence (AI). An O’Reilly survey of the data community, from data scientists to engineers to C-suite executives, showed that nearly half of respondents leverage data analysis, machine learning, or AI techniques to help them with data quality. 

The Data 2020: State of Big Data Study from SAP found that the most important technologies for activating data are analytics, the internet of things, machine learning, and AI. Using these tools to process, analyze, and leverage data is becoming more important, since 85% of respondents said they struggle with data from many different locations and sources. 

AI and machine learning help organizations make sense of data and focus on data quality. These considerations will likely continue to increase in importance.

More efficient practices are needed

Even while the use of data keeps improving, the reality is that many organizations spend too much time sifting through and preparing data before they can actually use it. The 2020 State of Data Science report from Anaconda revealed that an average of 45% of employee time is spent loading, cleaning, and preparing data in order to use it. 

Broken down further, respondents said that 19% of their time was spent loading data, 26% cleansing, and 21% creating data visualizations, among other tasks. Because of all this time spent trying to make sense of collected data, only 48% of respondents said they can actually show how data science impacts business outcomes.

Data privacy

Data privacy laws and regulations always seem to be changing. The General Data Protection Regulation (GDPR) was implemented in 2018 in the European Union, and more countries are likely to implement similar regulations. Gartner predicts that by 2023, 65% of the world’s population will see their personal data come under similar privacy laws.

The COVID-19 pandemic also means more businesses are focusing on security and risk management measures, updating their privacy strategies to fit within small budgets and combat new risks within the ever-changing data landscape.

This means marketers will need to keep privacy and similar consumer priorities top of mind moving into the years ahead.

BDEX is here along the way

No matter how 2020 changed the data landscape, BDEX continues to focus on data quality and real-time insights that connect you to your audiences at the right moment. Our data marketplace includes over 6 billion unique IDs, more than 5,500 data categories, more than a trillion data signals, and over 800 million mobile ID-to-email matches. 

We recognize that bad data is a major roadblock that can cost you a lot of time and money. We’ve implemented the BDEX ID Check so any bad data in our Identity Graph can be identified and filtered out.

To learn more about our data solutions, contact the BDEX team today. 

Established in 2014, BDEX is the first ever Data Exchange Platform (DXP). Combining hundreds of data sources in real-time into one unique data infrastructure, BDEX offers the most powerful, most accurate identity graph available in the U.S. market. BDEX empowers B2C companies to use the power of data to understand consumer behaviors and intents, helping them reach the right people at the right time.

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