Tag: data integration

enterprise data integration

7 Ways Enterprise Data Integration Enhances Business Value

data integrationIn today’s complex business world, companies across industries have started recognizing the true potential of data. Monetizing data has become essential for businesses to stay ahead of the curve. However, enterprises are facing critical challenges in today’s competitive business environment such as reshaping business operations, strategies, and sales on several fronts. This is where enterprise data integration services come to the rescue. 

It is high time that enterprises develop the ability to replicate and integrate their data. Businesses should accelerate the process of enterprise data integration with real-time and modern data integration solutions using analytics. Customer data processed in real-time is creating new opportunities. Enterprise data integration services can help businesses to reduce risk, improve operational efficiency, and identify new opportunities.

At Quantzig, we understand the difference that enterprise data integration solutions can create for companies. And to help enterprises excel in the competitive landscape, our team of experts have highlighted some of the crucial benefits of enterprise data integration that can help businesses to build a modern data architecture and reduce disruptions to production workloads.

Enterprise data management frameworks can help companies in leveraging data governance in real-time. Want to know how? Request a FREE proposal now!

What are the Benefits of Enterprise Data Integration?



Top 5 Challenges in Customer Database Management

Advancements in digital technology have enabled businesses to keep track of the details of their customers and their behavior. As the modern marketing era calls for companies to satisfy needs for multiple market segments, the companies should know more about their customers to cater to their personalized needs. Big data technologies, ERP systems, cloud technology, and AI have allowed companies to store large amounts of customer data and make an accurate analysis of each customer. Such analysis, in turn, allows the company to efficiently manage the customer relationship and thereby increase the customer lifetime value. However, managing customer Free demodatabase is not an easy task. So, what are the challenges faced by businesses in customer database management?

Challenges in Customer Database Management

Volume of data

As businesses start keeping track of multiple facets of a single customer data, the volume of data grows at an exponential rate. Businesses have to process large volumes of data in order to make critical datasets available to stakeholders in the time of need. Such data needs to be made available to multiple stakeholders across various devices and platforms, which, in turn, rapidly increases the storage and processing costs. Such large volumes of customer database will have to be managed with state of the art ERP systems and software.

Data collection and storage

The modern-day business environment is getting more competitive with each passing day, and customer satisfaction seems to be prioritized in their agenda. The rapidly changing customer behavior is causing problems for decision makers to decide on what’s best for the customers. The rise of omnichannel shopping has increased the amount of customer data that a business generates. Businesses are having a hard time managing such vast amounts of data. On top of that, they are also struggling to decide whether to take into account single customer view or cohort view while making an analysis.

Tracing customer journey

The most popular method of inspecting sales performance is by using customer journey cycle. To do so, companies need to keep track of multiple real-time customer data including interaction touch points, consumer sentiment, behavioral stages, and cross-team resourcing. Such charts paint a picture for decision-makers to take strategic decisions, which can subsequently improve customer experience. However, the challenge arises on methods to track the process of how consumers move from the stage of brand awareness to conversion. In particular, it is hard to pinpoint where exactly in the customer journey map a given customer can be located.

Choosing the right technology

Another problem faced by businesses in terms of customer database management is to select the right technology for their set of requirements. From multiple software’s and ERP systems to cloud-technology or on-premise technology, each has its own benefits and costs associated with it. Additionally, the technology may also need to be customized to match their requirements. Also, the type and form of customer data also dictate what kind of technology would be right for the organization. For instance, two completely different technologies would be required for processing structured and non-structured databases.

Privacy of customer data

One of the biggest challenges in customer database management is ensuring the privacy of customer data. Some customer data can be sensitive in nature, which is why issues in data security could cost companies millions in terms of lost customers or legal battles. Companies are continually battling to safeguard customer database against cyber-attacks and hackers.

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How Predictive Analytics is Driving the Future of the Connected Car Industry

The availability of a massive amount of data and exceptional mobile computing power has transformed the connected car technology. The traditional focus on vehicle management and infotainment systems has shifted towards developing the car’s ability to connect with the outside world. Multiple streams of communication such asFree demo IoT sensors, infotainment systems, and telematics systems in the connected car generate a colossal amount of data. Such datasets pave the way for the efficient use of predictive analytics tools to improve technologies associated with connected cars.

Ensure Passenger Safety

The AI system in a car has advanced to such a level that it can identify road signs, nearby cars, and road conditions to prevent a collision. The AI’s ability for collision prevention is augmented by employing predictive analytics in a connected car system. This can be possible by sharing vital information with nearby cars to warn each other when making abrupt maneuvers. Manufacturers are devising new ways to enhance collision avoidance systems by utilizing predictive analytics tools that utilize driver behavior data as an input.

Predictive Maintenance

The connected car system records and analyzes large data sets gathered from actuators, sensors, and machines. Such data sets can be useful in predicting requirement of full servicing, parts replacement, or other repair works. Apart from this, the data generated from connected cars can be shared with the manufacturer so that they can arrange logistics to deliver the spare parts to the required location by predicting its need.

Reinforcing Cyber Security

The idea of being able to control cars remotely may seem likely to invite security breach for malicious purpose and even terrorism. Predictive analytics is a powerful tool for identifying such cyber threats in its early stages. It utilizes user data, analyzes driver behavior to recognize patterns, and identifies behavior patterns that are inconsistent or different than the authorized user to stop unauthorized access.

Enter Quantzig:

Today, managers have access to a large stream of data, and decision-making on the basis of gut-feeling, the rule of thumb, and guessworks are largely eliminated with the advent of data analytics.

“Without big data analytics, companies are blind and deaf, wandering out onto the web like a deer on a freeway,” said a leading data analytics expert from Quantzig.

For more than 14 years, we have assisted our clients across the globe with end-to-end data management and analytics services to leverage their data for prudent decision making. Our firm has worked with 120+ clients, including 55+ Fortune 500 companies. At Quantzig, we firmly believe that the capabilities to harness maximum insights from the influx of continuous information around us is what will drive any organization’s competitive readiness and success. Our objective is to bring together the best combination of analysts and consultants to complement our clients with a shared need to discover and build those capabilities, and drive continuous business excellence.

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Managing Large Data Sets: How Quantzig’s Data Integration Solution Helped a Retail Chain Reduce Returns by 20%

Today, the retail landscape has reached its saturation point due to the presence of demanding customers who are more informed and discerning. The customers are leveraging the use of digital media to research online and make better-informed decisions. To increase their penetration levels, retailers are also relying on robust analytics to better understand customers, forecast needs, and demands. Consequently, retailers are adopting the use of analytics to optimize costs without compromising on the quality. Also, with the use of robust data integration, companies can design and implement data models and plan warehouses for companies.

Quantzig’s data integration solution helps clients reduce costs by effectively reusing data and knowledge. Moreover, Quantzig’s data integration solutions help businesses to seamlessly integrate data from existing on-premises system to the cloud, big data, and IoT systems in a cost-effective manner. Furthermore, Quantzig’s hybrid data integration enables the client to reduce complexity and improve overall optimization, thereby improving business agility.

The Business ChallengeQZ_DEMO

A leading retail chain, just like any other organization with a considerable number of employees, was facing challenges managing the data sets involved in their compliance training and product return processes. The client looked on to Quantzig to help accumulate and organize data in a more seamless and effective manner. The client wanted to maintain robust compliance guidelines and provide the necessary compliance training for employees. Moreover, the client was also facing challenges with tracking and monitoring returns.

Our Approach

To address such challenges, Quantzig’s data management experts collated data across a range of sources such as point of sale terminals, HR systems, customer surveys, and inventory management systems. Also, Quantzig’s data management experts created a dashboard to enable a more informed, data-driven decision-making process.


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Data Integration Solutions Benefits:

  • Create a comprehensive report that provided information on compliance course consumption
  • Gained access to compliance reporting with new reports generated every day
  • Identify locations that require more compliance training
  • Reduce returns by 20% and assess the performance tracking
  • Reduce time-consumption and man power compared to previous excel-based reports

Data Integration Predictive Insights:

  • Quickly spot the pain points and make informed business decisions
  • The users feedback showed a positive response with majority of stakeholders considering new reports as user-friendly and easy to navigate.
  • The client further was able to operationalize their business and reduce product returns by 20%.

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