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Posted 2nd October 2023

Data Analytics Trends That Are Transforming Commercial Landscape

Modern-day business operations call for modernized solutions because consumer needs keep growing and getting sophisticated, and there is a need to keep up. Thankfully, data technology keeps advancing, and entrepreneurs who understand what suits their operations leverage available solutions while looking out for emerging ones.  A perfect example is data analytics trends, which are necessary for […]

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Data Analytics Trends That Are Transforming Commercial Landscape

Modern-day business operations call for modernized solutions because consumer needs keep growing and getting sophisticated, and there is a need to keep up. Thankfully, data technology keeps advancing, and entrepreneurs who understand what suits their operations leverage available solutions while looking out for emerging ones. 

A perfect example is data analytics trends, which are necessary for businesses looking to exploit their full potential. A survey from 2017 showed that 48.4% of global firms reported measurable business value after investing in data analytics services, and the percentage grew significantly to 91.9% in 2023. 

Among the benefits accrued by organizations that have embraced data analytics include customer satisfaction, risk identification, improved decision-making, competitive benefits, and more. Several data analytics trends are shaping the rapidly evolving business world, providing actionable strategies such as helping organizations predict market dynamics and implement the best security practices. So, what is data analytics, and which trends should you look out for in 2023 and beyond?

Data Analytics and Its Latest Developments 

Data analytics involves using analytical techniques and tools to examine and interpret structured and unstructured data. The analytics aims to extract valuable insights businesses can use to improve operations or make informed investment decisions. 

Data analytics involves several steps to achieve better results, such as data collection, cleaning, modeling, visualization, interpretation, and presentation. The data analytics steps apply across all sectors, such as marketing, real estate, finance, manufacturing, and retail, among other industries that handle large volumes of data. So, which data analytics trends are redefining how things are done in the commercial landscape:

Self-Service Analytics

Self-service analytics have empowered businesses, helping them democratize data access for all involved. The trend allows users with less technical knowledge to access data from databases, cloud storage, or spreadsheets using user-friendly tools. Self-service analytics also have a collaborative feature, facilitating data and insights sharing between employees and management. 

Users can be trained to get the best out of the self-service analytics platforms. There is less involvement of data experts once self-service analytics have been implemented because it is not a complicated trend.

Business Intelligence 

BI is among the most widespread data analytics trends for business because of the valuable insights it offers. Data analysts use BI tools to break complex data into understandable bits. BI solutions can analyze data from various sources such as social media, sensors, spreadsheets, cloud storage, etc. 

Most BI tools have interactive tools, are user user-friendly, and mobile-friendly. Like most data analytics trends, BI also supports user collaboration, allowing users to share data in reports, charts, and other forms.

Data Clean Rooms

The concept of data collaboration between organizations and third parties is realized by adapting data clean rooms. Data clean rooms provide a safe environment for collaborating parties to analyze and process data without compromising its safety. Organizations embrace data clean rooms because they comply with industry regulations from bodies like CCPA and HIPAA, guaranteeing data confidentiality. 

Besides collaboration and security, other benefits of investing in data clean room services include creating a suitable space for more innovations, data monetization allowing the creation of additional revenue, fostering transparency among partners, and customization. 

ESG Data

Environmental Social Governance (ESG) is an aspect of data analytics that investors use to assess the suitability of funding a business based on its commitment to preserving the environment through adaptation of renewable energy and reduced carbon emissions, how the company relates with its employees, and the surrounding community, and its governance structure.

ESG data provides an ethical point-of-view of a business, which regulators, investors, media, and advocacy groups can use to rate a company’s impact on environment, social, and governance scopes. Therefore, a company’s overall success may depend on its commitment to implementing the three metrics of ESG trend.

Augmented Analytics

Artificial Intelligence and Machine Learning define augmented analytics, a trend that has gained traction over the years across different domains. Augmented analytics rely on AI and ML-powered tools to automate business operations, enhance data visualization, detect fraud and anomalies, and discover insights hidden in plain sight that wouldn’t be unearthed using traditional methods. Augmented analytics is also vital in creating predictive models, allowing businesses to prepare ahead and take advantage of emerging ventures. 

Data Monetization

Organizations aren’t the only beneficiaries of analyzed data if they sell it to third parties such as researchers, media, or similar businesses and earn extra revenue. Besides extracting value from their data, businesses can monetize their valuable findings in different formats, such as visual charts and graphs, text, spreadsheets, etc. 

Organizations can choose a subscription-based monetization model, where users can continue paying and accessing datasets as they are made available. More importantly, organizations can license their data so that users meet predefined terms and conditions before accessing and using it. Additionally, companies can offer data analytics services to outside clients at a fee. 

Natural Language Processing

NLP is a subset of Al that equips businesses with better customer understanding. It achieves this by studying human interactions on social media, phone calls, reviews, emails, and other unstructured data sources. A perfect example of NLP is streaming sites like Netflix and YouTube, where viewers can get video recommendations depending on their viewing history and preferences. Chatbots and voice assistants like Siri also demonstrate how NLP is used to communicate with customers.

Bottom Line

With the adaptation of data analytics on an upward trajectory, there is room for more trends to emerge. Analyzing large datasets is no longer challenging because of the influx of data analytics tools for all business sizes in the market. As a business owner, you should invest in market trends that show the promise of improving your brand for the better.

If you have difficulty choosing a suitable innovation, contact a data analytics form or expert for professional guidance. Join successful enterprises that have realized the importance of data analytics for a chance to boost your business in all aspects, and get a data analyst who can provide customized solutions for effective results. 

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