We Use The Most Effective Big Data Technology to Analyse The Growing Volume, Velocity and Variety of Data For The Greatest Insights That Find The Solution To Simplify Your Business Success

Big Data

Big data is a term that describes the large volume of data – both structured and unstructured – that inundates a business on a day-to-day basis. But it’s not the amount of data that’s important. It’s what organizations do with the data that matters. Big data can be analyzed for insights that lead to better decisions and strategic business moves. We work together with clients to build analytics-driven organizations. We meet our clients anywhere they are in their journey to become data-driven, providing everything from specific expertise on discrete issues to holistic transformations spanning strategy design, build, implementation, capability building, and ongoing support.

Data has intrinsic value. But it’s of no use until that value is discovered. Equally important: How truthful is your data—and how much can you rely on it?

Main V’s of Big Data

Variability

Variability in big data is an important factor, mainly about the number of inconsistencies in the data. These need to be found by anomaly and outlier detection methods in order for any meaningful analytics to occur. Big data is variable because of the multitude of data dimensions resulting from multiple disparate data types and sources. It can also refer to the inconsistent speed at which big data is loaded into the database.

Veracity

Veracity is an unfortunate characteristic of big data, refers more to the provenance or reliability of the data source, its context, and how meaningful it is to the analysis based on it. Veracity refers to the quality of data. Because data comes from so many different sources, it’s difficult to link, match, cleanse and transform data across systems. Businesses need to connect and correlate relationships, hierarchies and multiple data linkages.

Vulnerability

Big data brings new security concerns. In order to diminish this fear, organizations need to reassure customers about the safety of their personal data that it won’t be lost, misused or misplaced. This will require achieving a level of “data stewardship” far beyond a level that which is offered by most data businesses today. A data breach with big data is a big breach, unfortunately there have been many.

Volatility

Due to the velocity and volume of big data, however, its volatility needs to be carefully considered. You now need to establish rules for data currency and availability as well as ensure rapid retrieval of information when required. Make sure these are clearly tied to your business needs and processes with big data the costs and complexity of a storage and retrieval process are magnified.

Visualisation

Visualisation involves the presentation of data of almost any type in a graphical format that makes it easy to understand and interpret. Combine with the multitude of variables resulting from big data's variety and velocity and the complex relationships between them, and you can see that developing a meaningful visualization is not easy. This is very important because visualisation is often the only way customers interact with models.

Value

Arguably the most important of all, is value. The other characteristics of big data are meaningless if you don't derive business value from the data. Substantial value can be found in big data, including understanding your customers better, targeting them accordingly, optimizing processes, and improving machine or business performance. This is essential before embarking on a big data strategy to provide ever-increasing value for users.

Today, big data has become capital. Think of some of the world’s biggest tech companies. A large part of the value they offer comes from their data, which they’re constantly analyzing to produce more efficiency and develop new products.

Recent technological breakthroughs have exponentially reduced the cost of data storage and compute, making it easier and less expensive to store more data than ever before. With an increased volume of big data now cheaper and more accessible, you can make more accurate and precise business decisions.

Our cutting edge technologies and platforms provide a complete view of customer behaviour for improved tailored marketing and identify fraudulent activity. Monitor transactions in real time help organisations to take measure against fraudulent activities. Using the power of big data along with prescriptive analytics and comparison of historical data, we help clients predict and mitigate fraud.

Organizations are now tapping data science and artificial intelligence (AI) as a technology-enabled business strategy. Experimentation is accelerating across multiple clouds. The need for speeding through data preparation and exploration, modeling and training has never been higher. To succeed, a business must bring your algorithms to wherever data resides, Increase productivity of data scientists, analysts, developers and subject matter experts and operationalize the data science lifecycle from insight to prediction and optimization. With the help of Intuit ED service team you could find the solution that simplifies your business success.

Put your data to work for your business with our Data Analytics Services. Our full lifecycle of analytics solutions empowers your organization to not just visualize your data, but maximize its value. Our experts will work your team and data to help you define, design and build a transformative analytics roadmap to power innovation and scale as you grow.

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