Tag: Data Analytics

business analytics

5 Benefits of Business Analytics that Can Help You Drive Positive Business Outcomes

BUSINESS ANALYTICS

What is Business Analytics?

Business analytics refers to the skills, technologies, and best practices that empower organizations to iteratively explore and investigate past business performance to gain insights that help drive future business outcomes. Companies use business analytics for data-driven and smart decision making. Business analytics helps companies derive the desired outcome for businesses. It also enables companies to optimize and automate business processes and achieve a competitive advantage by offering insights that help them to :

  • Explore data and find new patterns
  • Conduct statistical and qualitative analysis effectively and explain the reasoning to certain results
  • Validate previous decisions using multivariate testing and A/B testing
  • Utilize predictive analytics and predictive modeling techniques to predict future results

Our business analytics solutions help companies in strategic decision-making. Want to know how? Request a FREE proposal now.

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Benefits of Business Analytics

Benefit #1: Encourages smart decision-making

Jetting off in the wrong direction can derail a business process. Fast decision making is easy, but smart decision making is more important for businesses in a short span of time. Business analytics empowers companies to easily access crucial data to make smarter decisions and stay ahead of the curve.

Benefit #2: Offers actionable insights through data visualization

Business analytics uses customized dashboards, charts, and graphs that can make decision-making more interesting. By leveraging analytics solutions businesses can gauge their performance and improve their bottom-line. The visual representations of relevant and extracted data provide detailed information about the target market and enable businesses to offer personalized services to customers.

Quantzig’s business analytics solutions help clients in tactical decision making to support real-time responses through customized analytics dashboards. Request a FREE demo below to know more.

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Benefit #3: Keep businesses updated

Today customers are digitally empowered and are easily influenced by better offers in the market. By leveraging business analytics companies can gain insights into customer sentiments and responses to any particular product or service. Business analytics can keep companies updated with the latest market trends and can protect against any unpredictable or volatile situation. This can also empower businesses to innovate and pre-empt their products according to customers’ needs and preferences.

Benefit #4: Makes business processes efficient

Since its advent, business analytics has improved the efficiency of businesses significantly. It has the ability to analyze clusters of data at a faster rate and with maximum accuracy. Consequently, this can help companies to achieve their business goals. Also, by leveraging various analytics tools, companies can encourage a culture of cooperative teamwork where employees can contribute to data-driven decision making.  

Are you finding it difficult to analyze trend data and assess the likelihood of future outcomes? Our business analytics solutions can help. Get in touch with our experts right away!

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Benefit #5: Helps in quantifying company values

Every successful business has a set of core values that determine their success ratio. By leveraging business analytics, companies can gauge how these values are quantified and conveyed in a tangible way to drive maximum profit. Quantified values can help businesses in improving their analytical process by defining a common goal that should be followed by everyone associated with the business.

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Evaluating the Importance of Data Analytics and Visualization for Businesses

When it comes to successfully positioning your organization in the competitive market, data analytics and visualization act a key ingredient. Data visualization using appropriate data analysis methods can provide valuable insights into business operations. Such insights can be incorporated by businesses in the decision-making pipeline to make data-driven decisions. Leveraging such data analytics and visualization solutions can help companies to analyze their data irrespective of the size, scale, type, and domain and improve their decision-making capabilities.

Data analytics and visualization have become a necessity for companies to manage risks and comply with the changing regulatory landscape.

Therefore, it is imperative for businesses to realize the importance of data analytics and visualization as visuals are immensely capable of predicting all possible outcomes and make complex decisions to yield favorable outcomes. In this article, our team of experts has highlighted how data analytics and visualization techniques can be utilized to make the most of the statistical data, old experiences/learnings, and fresh ideas to launch new products.

Extracting insights from disparate datasets can be a difficult task for companies. But data analytics and visualization techniques can help. Request a FREE demo today!

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How can data analytics and visualization help businesses?

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web mining

Web Mining: A Key to Boost Your Business on Web

What is Web Mining?

When data mining techniques are applied to web data to identify useful patterns, it is called web mining. Web mining integrates the information collected from world wide web and information fetched from data mining techniques to quantify the success of a marketing campaign for any business. Web mining is one of the web analytics solutions that help organizations in analyzing the effectiveness of a specific website, understand consumer behaviour and competitors’ strategy efficiently. The information collected through web mining offers actionable insights into the web structure, content, and usage.

Types of Web Mining

Web Mining-Type #1: Web Content Mining

Web content mining aims at collecting multimedia documents such as video, images, and audio that are hyperlinked or embedded to the web pages. Web data mining deals with unstructured or semi-structured data and requires a creative approach to data mining techniques. In the last few years, the activities in the field of web content mining have expanded rapidly due to the exponential growth of data on the web. However, due to the lack of structure of web data and its heterogeneous nature poses several challenges in the web content mining process.

Web mining solutions can help in enhancing your website’s performance significantly. Request a FREE proposal now to know how!

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Web Mining-Type #2: Web Structure Mining

Web structure mining aims at analyzing the link structure of the web and identifying more desirable documents. Web structure mining assist companies in identifying similarities between different websites. It aims at generating a structural summary about the web page and the website. The main aim of web structure mining is to focus on the inner-document structure as well as on the structure of the hyperlinks at the inter-document level. Web structure mining uses topology of hyperlinks to categorize and deliver information on the relationship and similarities between multiple websites.  

Web Mining-Type #3: Web Usage Mining

Web usage mining aims at predicting the behaviour of users while they interact with the world wide web. It helps in discovering the navigation patterns of users. Also, it fetches useful information from the user interactions on the web that further helps in understanding consumer behaviour and buying patterns. Furthermore, such insights can help in providing personalized services, site modification, and overall system improvement.

Request a FREE demo to find out how our customized analytics dashboards can help you categorize your web pages and offer personalized services to your users.

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Advantages of Web Mining Solutions

Benefit #1: Improves business on the web

Web mining helps in analyzing click-stream data and unveiling e-business opportunities in real-time. It aids in targeting the right customers at the right time by understanding their needs. Also, web mining solutions help in customizing services according to customers demand which further helps in improving marketing strategies. Furthermore, web mining solutions help in improving the effectiveness of a website by offering what users want at the right time.

Web crawling and text mining solutions can help in improving cross-selling opportunities. Want to know how? Read our latest success story here:

Web Crawling and Text Mining Engagement for A Leading Digital Media Industry Player Helps in Increasing Cross-Selling Opportunities

Benefit #2: Helps in analyzing customer behaviour 

By leveraging web mining solutions, companies can understand and analyze several concerns such as the relationship between customer’s present and past behaviour and their loyalty towards the website. Analyzing customer-centric web behaviour can be helpful for companies in improving the website segmentation based on customer behaviour and preferences. Also, it can help in offering personalized services to customers. Furthermore, web mining guides in predicting customer’s future behaviour which is very important for a website’s future content design and planning.

Are you finding it difficult to analyze the effectiveness of company communications and customer interactions on the world wide web? Web analytics solutions may hold the key to success. Get in touch with our experts.

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Benefit #3: Assists in analyzing proxy servers

Web mining has the ability to help in identifying user behaviour on a particular website. Businesses can leverage web mining solutions to perform investigations on their own website and can yield actionable insights into the needs of users and accommodate them. But apart from this, what is equally important is analyzing a user’s behaviour on the proxy servers. Web mining can efficiently do this and can help in generating an overview of customer behaviour on the internet.

Quantzig’s Advantage

Businesses that run online receive heavy traffic on a daily basis and the immense volume of continuous data makes it extremely challenging for businesses to track their visitors and analyze website statistics, potential consumers, and prospective buyers. Quantzig’s data analytics services and web mining solutions help companies in managing large volumes of web data and set up customized dashboards to derive real-time insights to facilitate data-driven decisions. Quantzig’s data analytics solutions provide companies with the required technologies, capabilities, and frameworks to handle the sheer volume and variety of data while ensuring privacy and security of information. Quantzig with leading data-governance practices deliver best-in-class frameworks for data visualization and multi-dimensional data aggregation that further helps in better insight generation.

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!

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What are the Benefits of Enterprise Data Integration?

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A Definitive Guide to Metadata Management

What is Metadata Management?

Metadata is like a golden thread that interconnects different functions of an organization. It comprises heterogeneous, heavily distributed and hybrid mixes of data from cloud systems. Metadata management deals with the management of complex data through analytics, operations, discovery, collaboration, and compliance. Metadata management acts as a key enabler in the data-driven decision-making process of a business. For any organization, all the data-driven actions pass through metadata when the customers browse through the website, run a query or make a virtual view.

Businesses need to understand and analyze their data to survive and grow. Metadata management can provide the required processes to gain this insight and succeed. Want to know how? Get in touch with our experts.

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Why is Metadata Management Important?

With the growing volume of data, metadata management has gained huge importance. Although it sounds a little geeky, it is a crucial component of records management and data governance. Here are a few reasons why metadata management is important:

Reason #1: Increases the longevity of datasets

The lifespan of a particular dataset can be very short due to the unavailability of relevant metadata. The growing complexity of data with the increasing constraints of time and funding also contributes to the shorter life span of the datasets. But metadata management can counteract this tendency of data degradation efficiently. 

Reason #2: Facilitates data reuse and data sharing

Metadata management ensures that the complex and complicated data is easily analyzed, interpreted and shared. It provides detailed instructions to interpret unfamiliar data accurately and helps in data integration.

Reason #3: Helps in maintaining historical records of long-term datasets

The datasets may encounter inconsistency in methods and instrumentation during the ongoing long-term projects. Metadata management helps in maintaining the historical records of such long-term datasets, thereby assisting in data governance. Furthermore, metadata management is important for data integration that contains different parameters but shares common temporal or spatial domains.

Wondering how metadata management system can enable you to build an enterprise model based on the metadata developed from various attributes such as your data integration tools and data warehouse? Request a FREE proposal now!

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Reason #4: Assists in improving interoperability and integrating resources

Metadata management makes it easy for humans as well as machines to understand the different resources. Also, it facilitates the understanding of how data is exchanged among many systems with different data structures, operating systems, and interfaces.

Reason #5: Protects resources and their future accessibility

The digital information today has become very fragile and is susceptible to corruption. Metadata management helps in archiving and preserving such information by tracking the lineage of the information and describing its characteristics. Also, it helps in understanding the behavior of the information to prevent its replication in the future.

Steps to Effective Metadata Management

Step #1: Meta repository creation

There are several repository tools available in the market that profess to create metadata repository. But all such tools may not suit your business. Most of these tools focus on one specific aspect of metadata. Therefore, you need to collect a set of metadata about each element of your business and relevant to your organization in the following six categories:

  • Business metadata
  • Core and technical metadata
  • Data quality metadata
  • Search metadata
  • People metadata

Step #2: Identify core attributes

Develop key business queries to get a fair idea about the underlying attributes which is necessary for analysis. It is important to identify and understand such attributes as they play a crucial role in downstream analytics.

Step #3: Acquire the metadata

Once your foundational capabilities are established, the next step that comes is implementing the meta acquisition process. Most of the categories of metadata need proper processes for acquiring it from the people who work in various functions of the organization.

A properly built metadata management model has the potential to give a 360-degree view of how operating systems in your organization are connected together. Such models can help users to solve issues based on different attribute types and names. Request a free demo to know more about how metadata management models can help in creating custom metadata types.

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Step #4: Create a protocol and maintain consistency

Data keeps on changing constantly with the growth of new business initiatives every day. Such changes result in long-term data instability. Therefore, it is necessary to create a more efficient process to monitor data streams for change. This is the most difficult but important step in establishing an effective metadata management process.

Metadata Management Vs Master data Management

Metadata management talks about the content in the data that is gathered and helps the organizations in uncovering the facts hooked to their data. Through metadata management, users can decode the data in terms of what it represents and derived. Metadata management consists of all the entities and attributes, programs, calculations, reports etc. The nature of metadata depends on what it talks about.

Master data management talks about the data that consists of entities like products, services, people, organizations etc. It usually talks about non-transactional data which usually covers:

  • Internal entities such as employees, departments, and products
  • External entities such as suppliers and customers
  • Information of organization such as reporting hierarchies and the chart of accounts.

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Reasons Why Fraud Analytics is the Need of the Hour

What is Fraud Analytics?

Fraud analytics is an umbrella term that comprises numerous quantitative sciences like business intelligence and data analytics in order to better understand fraud. Furthermore, fraud analytics helps in developing effective fraud detection solutions through data science.  Many organizations practice traditional anomaly detection methods for fraud prevention and detection. But unfortunately, they are not powerful and function under certain limits. When analytics is added to such traditional fraud prevention methods, it improves the capabilities of fraud prevention and gives a new dimension to the fraud prevention techniques. Additionally, fraud analytics empowers organizations to have proper control over every ongoing activity.

Reducing exposure to risks, fraud, and credit losses is a daunting task for businesses. Are you facing the same issue? Get in touch with our experts to know how our fraud analytics solutions can help.

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Fraud analytics can prevent businesses from the cost of fraud which is equivalent to a financial iceberg, some of the direct losses are clearly visible but there is a huge mass of hidden harm that companies cannot see.

Why is Fraud Detection Important?

For an organization, fraud detection forms an integral part of the risk analysis process. It provides the ability to quickly filter out fraudulent sources which prevent an organization from any high-level risk in the future. Here are a few reasons why fraud detection is important:

  • Decreases exposure to fraudulent activities
  • Reduces costs associated with fraud
  • Identifiesvulnerable employees at risk of fraud
  • Improves organizational control
  • Enhances the organizational result
  • Boosts the confidence and trust of the shareholders

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Are you facing difficulties in financial risk monitoring and management? Leveraging fraud analytics solutions may help. It has the potential to manage risks more effectively to maximize ROI. Request a free proposal to know more about our portfolio of fraud analytics solutions.

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Benefits of Fraud Analytics

Helps in identifying hidden patterns

Fraud analytics along with machine learning has the potential to help organizations in identifying new trends, patterns, and scenarios under which frauds take place but traditional approaches to fraud prevention miss such things.

Aids in integrating data

Fraud analytics plays a crucial role in integrating data. It combines data from public records and multiple sources that can be integrated into a model.

Improves existing efforts

Fraud analytics instead of replacing traditional rule-based methods just adds up to existing efforts of the organization to provide improved results.

Harnesses unstructured data

Unstructured datasets are the most complex thing for companies to deal with. Fraud analytics helps in deriving the best value from such unstructured datasets. Data warehouse of any organization consists mostly of structured data, but unstructured data is the source where more fraudulent activities take place. This is where fraud analytics plays an important role in reviewing the unstructured data and preventing fraud.

Our recent success story highlights the importance of fraud analytics in the telecom sector and explains how leveraging fraud analytics solutions helped a telecom industry player to overcome revenue losses. Click here to read the full story.

Methods of Fraud Analytics

Perform SWOT

With the increasing importance of fraud analytics, organizations too have realized the important role it plays in the process of growth. But many of these organizations are opting for expensive fraud detection solutions that do not match with the strengths and weaknesses of the company. Therefore, it is essential for the organizations to do SWOT analysis before starting with the fraud detection process in order to make it work to the fullest.

Sampling

Sampling is an effective method of fraud detection that involves a lot of data. However, it has its own disadvantages too. Sampling may not be able to control the fraudulent activities completely as it takes only a specific population into consideration.

Ad-Hoc

Ad-Hoc is nothing but identifying fraudulent activities by the means of a hypothesis. It offers the ability to explore and test the transactions in order to detect the fraud. Also, you can conduct a hypothesis to test and find out if there is any abnormal activity occurring and then you can investigate the same.

Repetitive or Continuous Analysis

Repetitive analysis generally refers to creating and setting up scripts to run against a huge volume of data to determine the frauds as they occur over a period of time. This method of fraud analytics helps in running the script every day to go through all the transactions. Furthermore, this provides periodic notification regarding the frauds. This method can help in enhancing the overall efficiency and consistency of your fraud detection processes.

We understand the challenges companies face in the management of claims, underwriting, actuarial, pricing and marketing functions. Our analytics solutions provide best-in-class frameworks to determine the level of risk in claims, creating individualized and relevant policies to suit and benefit customers, and identifying key indicators that provide insights into risks and quantify predicted loss severity from loans and claims. Request a free demo below for more insights.

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Quantzig’s Data Analytics Engagement Helps A Leading Healthcare Industry Player Realize Over 5% in Profits and Improve Customer Engagement

2018 has been the year of emerging healthcare industry trends and it is expected to transform the industry in the years to come. This year, however, companies will witness rapid changes with transparency becoming one of the key concerns for healthcare providers. Startups of today are bringing innovative changes to the market by combining technologies like AI and machine learning with traditional practices.

With continued vertical integration, mergers and acquisitions, and big tech companies making their move to the healthcare industry, it’s becoming clear that the pace of disruption in healthcare is accelerating. Moreover, newer healthcare industry trends and the advent of technology have brought the healthcare industry to the zenith of modernization and innovation. But the constantly rising competition in this sector calls for healthcare companies to generate situational-driven strategic insights, cope with upcoming healthcare industry trends, and act with deliberate speed to acquire more customers and retain the existing ones. As far as the healthcare marketers are concerned, it is high time that they identify the ongoing healthcare industry trends, rethink underlying assumptions, and re-engineer their approaches to marketing to stay relevant in the market and create a better customer experience.

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4 Effective Ways Healthcare Data Analytics is Reducing Healthcare Costs

Despite its promising growth prospects, healthcare service providers are hard pressed to find solutions to multiple complex issues including regulatory and policy changes, medicinal and technological advancements, rising costs, staff, and trained employees, maintain efficient operations and services, and support other healthcare initiatives. With increasing concerns for living healthier, longer, and lead more active lifestyles, healthcare costs have increased. Research reveals that the spending and healthcare costs often rise at rates more than the rate of inflation and is expected to increase even more in the years to come.

With the rising healthcare costs, co-pays and deductibles have become expensive and employers are burdened to take a bigger cut of their employees’ wages to pay for insurance premiums. This surge in healthcare costs will soon become a big barrier to the growth of the overall healthcare industry. Therefore, leaders must find alternative methods to combat rising healthcare costs. They must do the appropriate research to find funding, grants, and contributors to help them conduct research, set up programs and implement processes at the pace of change.

At Quantzig, we understand the impact that costs have on your business plans. And to help companies excel in an ever-competitive marketspace, our team of experts has highlighted four effective ways in which healthcare data analytics can reduce the Contact USrising costs of care.

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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.

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