How to Harness Third-Party Data for Big Data Analytics?

Background photo created by biancoblue
Background photo created by biancoblue
Background photo created by biancoblue
Background photo created by biancoblue

Tapping third-party data can unleash huge possibilities in data science bringing untapped opportunities.

How do organisations avoid getting lost in the data web? By mastering Big data, and the third-party data. However, mastering the third-party data can be very challenging, call its adherence to strict data privacy norms which cannot be missed. Data is growing and so are the opportunities that can be harnessed from them. To gain most from third-party data silos, business leaders must strategize to navigate the complexity that surrounds this data goldmine.

Third-Party Data Mining

• Addressing Data Gaps

The lacunas of internally data mining can generate gaps, causing companies to look for new data sources to incorporate insights. These external data can include almost anything, weather data, satellite imagery to historical demographics.

• Facing Micro Local- Challenges

In the interconnected eco-systems of the modern era, businesses increasingly operate in channels that brings together suppliers, regulators, resellers, channel partners, and other stakeholders. These global channels of business essentials are potentially affected by microeconomic, political, and/or environmental factors.

Analysing external data can help businesses function amidst uncertainties

• Mitigating Data Risks

Analysis of third-party data can help companies foresee the risks and opportunities that they may encounter operating in hyperlocal environments. External data assist to illuminate how factors such as shifting competitor initiatives, geopolitical events or environmental changes, can affect a business in a micro and a macro level

Businesses and technology professionals acknowledge the volume of big data being created, shared, and stored is increasing at an exponential pace. According to the Cisco Annual Internal report, big data stored in data centres will nearly quintuple by 2021 to reach 1.3 zettabytes globally by 2021. (imagine this – One zettabyte is equivalent to one trillion gigabytes!)

The potential business takeaways from analysing third-party data grow bigger day by day. This leaves no surprise that companies wishing to adopt data science and big data analytics want to make use of third-party data for long term gains.

Gaining Maximum Returns from External Data Silos

As discussed, external data sources are information goldmines, untapped. ,Takeaways include improvement in business decisions, gaining new revenue streams, targeted product and service delivery, risk mitigation, and readiness to meet future challenges. Here are a few examples where businesses can gain from harnessing third–party external data sources–

• Creating personalised marketing offerings

External Data in use- Customer demographics—age, income sub-group, location, social media posts.

• Predicting employee attrition

External Data in use- Job website postings, social media data (like LinkedIn)

• Analysing future agricultural produce

External Data in use- Geolocation data, Weather data, historical crop yield data.

Though external data poses its benefits, enterprises must address the challenges that come along the way, owing to data quantity, data availability, and the ultimate data access.

Pathways to connect to third-party data sources

Connecting to external data sources can be daunting, organisations need to address challenges that range from the size and complexity of the data-provider market, identifying the right data sources and partners, negotiating data acquisition, data usage restrictions, and so on.

Accessing the external data eco-systems means identifying, evaluating, procuring, and preparing external data warehouses in a timely and consistent framework. Businesses need to make constant efforts to engage with stakeholders, data partners in a bid to integrate external data into their daily operational processes. There are a variety of ways  to connect to the external data ecosystem which include-

• Simple data services- Collaborating with data brokers who collect data from multiple sources and offer it in collected and conditioned form in exchange for a sum payment.

• Smart data services– Harness the credits of IoT sensors to collect live data by object tagging.

• Adaptive data services- This includes access to primary and secondary surveys. Request customers to submit data about specific analytical requests.

In the exciting future to encounter, businesses would be making rampant data deployments from third parties. To gain maximum returns from their data analytics efforts, organisations must consider uplifting their efforts to identify, evaluate, and contract for new external data through data ecosystems.

For many, the effective use of external data is a critical new frontier.

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