Loathe or love it; we are in the reign of big data analytics. By the end of this year, this market is set to surpass a value of $100 billion, and it will grow by billions more within the next decade. Data is the new gold, and it’s important to understand the latest AI & data analytics trends to capitalize on its financial potential and keep at the leading edge.

Here are some of the latest trends in big data analytics that won’t be going anywhere anytime soon.

1. Adaptive artificial intelligence

Adaptive AI is the future of machine learning as well as big data analytics. This technology enables algorithms to learn on the fly – not just from initial training data sets – and accommodate changes as they surface.

Some of the benefits of this new form of AI over conventional ML models include:

  • Enhanced learning prowess
  • Better flexibility
  • Improved accuracy

All, in all, adaptive AI would mean a faster turnaround in big data analytics and the ability to accommodate changes in the data as they crop up.

2. Collaborative business intelligence

Approximately 3 in 4 workers say proper collaboration and teamwork is a top priority, with 56% of companies relying upon various online collaborative tools as we speak.

Collaborative BI has been the logical next step in business intelligence. It entails the fusion of traditional BI tools as we know them with online collaboration solutions. This enables more unified access and interpretation of a business’ big data pipeline.

3. Natural Language Processing

NLP makes up one of the hottest AI & data analytics trends, and it entails AI models being able to understand human language and offer appropriate feedback.

Here are a couple of ways NLP is finding purpose in big data analytics today:

  • Businesses are using NLP models for sentiment analysis
  • The power of NLP is also being levered for chatbots
  • Moreover, many brands use NLP models for social media listening

4. Data democratization

The benefits of big data cascade right from the top of a company’s hierarchy down to its foot soldiers. It is, therefore, important that every member of an organization, regardless of tech-savviness, can understand big data and apply it to derive business value.

As a result, we’re seeing more accelerated attempts at data democratization as businesses scurry to unlock the true power of big data.

5. Predictive analytics

Proving a crystal ball into future business possibilities, predictive analytics is also among the trends in big data that are blowing up this year. These strategies entail picking out patterns from past data to anticipate the future.

Predictive big data analytics is finding purpose today in the following ways:

  • Sales forecasting
  • Churn prevention
  • Customer targeting
  • Risk assessment, etc.

6. Data security

With big data comes big risks. Statista Research reports that over 15,000,000 data breach cases were recorded in the latter four months of 2022 alone.
In light of this growing threat, big data analytics are also responding in kind.

We’re seeing a rollout of advanced defence measures, some of which include the encryption of both data that’s in transit and at rest. Endpoint validation and filtering and big data cryptography also continue to heavily play a part in protecting big data.

7. Data lakes

Up to 90% of our planet’s data could be unstructured. It is, therefore, understandable why data lakes are becoming the way to go as far as the latest AI & data analytics trends are concerned.

This data architecture is becoming more popular in data warehouses, allowing organizations to analyze all types of data in one place, namely:

  • Videos
  • Audio files
  • Images
  • Textual data

8. Cloud computing

Corporate data stored in the cloud accounts for 60% of all business data worldwide, with 9 in 10 large enterprises putting in place multi-cloud big data technologies.

In my book, big data and the cloud are a match made in heaven. The biggest benefit I see here is the accessibility that the cloud offers, ensuring that every business, regardless of size, can fully reap the benefits of big data technologies, their infrastructural capacity notwithstanding.

9. New data sources

The sources of big data continue to increase with the progress of technologies. As innovations hit the market, so too do big data analytics make room to accommodate them.

For example, modern big data analytics technologies are now expanding their data sources also to incorporate modern innovations such as:

  • Smart devices
  • Social media
  • Sensors
  • Generative AI and much more

10. Embedded analytics

The conventional workflow and big data technologies haven’t always co-existed. Embedded analytics is changing the status quo, allowing businesses to blend these technologies with software tools within the natural workflow.

Set to topple $77 billion by the turn of 2026, the embedded analytics market ranks as one of the most profitable trends in big data. Expect to see even more experimentation on this front.

Big Data Analytics- Always on the move

Blink and you’ll miss it. AI & data analytics trends are constantly in flux, propelled by the concept of accelerating change. The more these technologies get implemented across different fields, the more they’ll keep evolving to match these specific niches’ needs. Nonetheless, these ten trends in big data serve as the fabric for big data innovation. They will likely survive the test of time and provide a base for progressive updates to build upon.