Tag: big data analytics strategy

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5 Ways Big Data and Analytics Are Revolutionizing the Food Industry

The food industry is one of the largest sectors in the industrial world. With the increase in global competition, the food industry is facing numerous challenges like reducing supply chain waste, optimizing supply chain efficiency, boosting sustainable growth, implementing green policies and finding a competitive advantage. With growing complexities, businesses in the food industry need to keep close tabs on managing product and data throughout the supply chain.

Inefficient supply chain leads to low-profit margins and more wastage. Furthermore, if the supply chain is not optimized, it can result in the inability to adapt quickly to a problem and can increase operational costs. Therefore, players in the food industry must leverage the benefits of technology like big data and analytics to gain better insights into the ability to track and monitor supply chain activities in real time.

At Quantzig, we understand that to ensure the efficiency and performance of your supply chains, from sourcing to manufacturing to delivery, optimization is required. And to help food industry businesses thrive in the competitive landscape, our team of experts has highlighted five ways in which big data and analytics can help companies in the food industry to become market leaders. 

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benefits of data analytics

Top 3 Benefits of Data Analytics That Can Take Wearable Technology to the Next Level

From fitness and activity trackers to “smart clothing” and smartwatches, the possibilities are practically limitless within the industry for wearable technology. And this growth is further enhanced by the promise of high monetary rewards. But design and data collection are only a small component of the potential that wearables offer to both companies and consumers. Taking wearable technology to the next level of usefulness requires companies to build in additional analysis features that increase engagement levels, improves the usefulness of the wearable technology, and provides an unparalleled experience to the consumer. In other words, the benefits of data analytics can help companies to effectively determine what the wearable technology is actually doing for their consumers. But the question that arises here is, what are the benefits of data analytics and how can it help wearable technology to become even more popular. This article has answers to this question. Here, we have discussed in detail some of the significant benefits of data analytics that have potential to take wearable technology to the next level in 2019.

Benefits of Data Analytics

Detailed insights from collected data

One of the most crucial benefits of data analytics is that it can turn collected data into the foundation needed for actionable insights, and in doing so provides additional company and consumer benefits. For example, a sleep tracking device might collect data on how and when a consumer is sleeping. But without the analysis of the collected data, the device only helps in identifying the hours that a consumer sleeps or fails to reach a REM cycle. Does this knowledge help consumers in any way? The answer is simple, no! It is in this context that the real benefits of data analytics are realized.

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Personalized services based on habits 

By leveraging the benefits of data analytics, wearable devices can provide personalized offers to consumers. By analyzing the data captured by wearable technologies, companies can create marketing offers that are customized to each consumer. For example, a step-tracker can reveal that a consumer takes the most steps around lunch time. By leveraging this information viaRequest Proposal personalized offers, companies can encourage the consumer to take more steps throughout the day. 

Improved employee health and productivity

One of the key benefits of data analytics is their ability to improve the health and productivity of employees. Wearable technology can collect the data needed for a company to analyze the productive hours of the day of their employees. Additionally, the devices can also monitor employees’ health, so that the company can mitigate risks associated with lack of sleep, high levels of stress, and other health symptoms that contribute to an ineffective and unhappy workforce.


Want to gain better insights into the benefits of data analytics and its ability to enhance the capabilities of today’s wearable devices?

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3 Common Mistakes to Avoid in Big Data Analytics

Today, big data analytics is one of the most crucial processes for any business, big or small. For data scientists, it acts as a pair of glasses that helps them see the actual reality of a business’ performance, beyond scattered numbers in graphs. A proper, solid, and reliable analysis allows you to make fact-based and rational decisions, but if mistaken, advanced data analytics can lead you astray and you might end suffering a huge loss. So, it can be safely presumed that it is not enough to have good quality data unless you use the datasets efficiently. However, there are many hurdles that businesses might encounter along the way. While implementing a new strategy to strengthen your business with advanced data analytics, mistakes can prevent you from realizing its complete potential. So, in this article, we have summed up some of the common blunders businesses should avoid while developing a big data analytics strategy.

Mistakes to Avoid in Big Data Analytics

Being rigid in processes and products

If you are rigid with your process and product, you are committing a big mistake. You should begin your project in a way that is both strategic in vision and agile in execution. Therefore, you need to pick technologies that are open and expandable. For example, you must avoid vendor lock-in by using open source tools. For obtaining optimum results from advanced data analytics, it is important to foster a culture that fosters failing fast and learning from mistakes. You must avoid letting egos drive your project and understand that if your team experiments on ten things, eight of them might not work. You should get people on board in your data project team who can thrive in this sort of DevOps style of work.

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Neglecting security and governance at the beginning

Today, security and governance are extremely important, as privacy is one of the major concerns in almost every industry. Businesses still tend to start big data analytics projects as pilots, with just a handful of people working on them, and without security and governance baked in. This is a huge mistake when it comes to big data analytics. You must get compliance, governance, and security conversations started on the very first day of the project. You must carefullRequest Proposaly choose the right governance strategies, as well as the right technology of governance.

Relying on the same KPI’s always

As things are constantly changing and your business is subjected to constant dynamics, so you must learn to adapt to the ever-changing environment. This is how you can prosper. So, try not to hold on to the old performance indicators that are used to measure your success in the past. You need to use newer and more suitable tools to make advanced data analytics tools reflect the current performance of your business and identify what really drives your business forward.

Quantzig’s Advantage

Being a leader in offering big data analytics services, Quantzig helps businesses to manage, store, and integrate huge datasets. Also, we help businesses to gain predictive insights that facilitate proactive business decisions and pre-emptive planning. Additionally, Quantzig promises to deliver best-in-class frameworks for multi-dimensional data aggregation and utilizes visualization-based data discovery tools for insight generation.


Want to leverage Quantzig’s analytics solution and BI visualization services for strategic decision making?

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3 Ways Advanced Data Analytics Can Drive the Next Wave of Growth for Transportation and Logistics Companies

Today, transportation and logistics (T&L) companies have embraced advanced data analytics in their operations since it allows them to run sophisticated networks globally. But unfortunately, the investments made in advanced data analytics is not satisfactory. Now, it is time for that to change if the companies in the T&L sector really want their sales performance to grow. The commercial analytics capabilities of this sector lag average performance, which is primarily because of the reason that sales forces in this sector rely heavily on outdated processes and lack proper insights into preferences of their customers and growth opportunities. Here rises the need for big data analytics for T&L companies. They already have enough data and can utilize big data analytics extensively to earn desired outcomes. With years of experience in offering data analytics solutions to businesses, we have noted that companies in this sector who embrace advanced data analytics can generate an additional 2-5% percent return on their investment. In this article, we have summed up three things that T&L companies need to do to realize the true potential of advanced data analytics:

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Top 3 Reasons Why Every Business Needs a Big Data Analytics Strategy

Change is inevitable and adapting to change is the only way companies can sustain themselves in a competitive marketplace.

With advancing technology, business processes face the need to be regularly updated and analyzed to boost efficiency. Technology has made data one of the most important assets for any company. It is one of the keys that can boost the competitive advantage of one business to a great extent. In fact, if you are looking for ways to boost the productivity of your business, then maximizing the amount of data being analyzed is one of the most crucial strategies for success. Speaking of data, one of the hottest trends in data analysis this year has been big data. By utilizing a big data analytics strategy, companies can easily develop an effective strategy for their business’ successContact US by analyzing their unstructured data. In this article, we have highlighted the key reasons that make big data analytics strategy important for enterprises. (more…)