Over the last decade, data has done more than explode, it’s completely changed the way companies operate. When technology made it not only affordable, but advantageous to store a wide variety of information, Big Data took the business world by storm. Once all of that data was wrangled and stored, organizations of all sizes collectively came to terms with a new challenge: creating value with all of that information. The truth is that the ambition to collect data had far outpaced business’s abilities to analyze it. Organizations across all industries had an extremely wide range of data inputs and an equally distributed approach to storing all that data.
It's a fascinating time to be in the data and analytics space. Companies are more aware than ever of the impact data can have on their business. This year, our tried and true predictions that we have been making for some time now are coming true right before our very eyes — every company is becoming a data company.
In the coming years, the true value of data will be realized and companies will adjust their business in anticipation of this value. Data will drive processes and operations through analytics and BI. Developers and data teams will emerge and create clear and efficient insights that will drive decisions. Analysts and business users will be handed coherent answers from complex data queries that will lead the way to more successful businesses.
The rise of cloud computing has led to an increase in complexity for businesses. Your company probably has data in a wide variety of locations: on-premises and a couple of different cloud sources. How do you create a unified strategy for data spread across all those locations? What about empowering individuals and teams to pull insights out of that data? How are you handling live data sources with constantly updating streams of information?
For customer success teams, the only constant is change — new business priorities, new processes, new product features, new customer objectives, etc. The best success teams put strategies and processes in place to identify key metrics, prioritize operations and scale effectively. The reward for managing it all correctly is happy, loyal, and profitable customers.
Modern customer success teams are swimming in data: product usage data, account data, user data, billing data, etc. All that information comes from different places and isn’t structured in a way that makes it easily understandable. Organizing it all into a single location is a chance for an opportunistic team to understand the overall customer experience and provide proactive recommendations throughout the relationship. But without the right strategy, that analysis can be overwhelming and distracting.
It has become evident that Big Data is the dynamo that drives enterprise growth. At the end of 2018, the adoption of Big Data in enterprises reached 59%, with a compound annual growth rate of 36%. This trend will continue to accelerate, powered by the ascendancy of cloud-based data warehousing, analytics platforms, Artificial Intelligence (AI) and machine learning (ML) technologies. Adoption rates like these indicate that Big Data and analytics usage are now mainstream.
Business Analytics is used to develop new business insights and to understand business performance. There are four key approaches, each with their own unique business benefits. So, how do you know which is right for your organisation? Read on to find out.
The 4 different types of Business Analytics
What they mean in plain English
Mondelio Worldwide is an Australian company having commenced operations in 1982. Mondelio's single focus is to provide predictive data modelling and data analytics services to organisations throughout Australia and overseas.
Mondelio has partnered with Stonebridge Consulting, Naveego and Sisense expanding our product offerings to the wider APAC market.