WhereScape is thrilled to invite you to...
WhereScape / Mindfull Big Data alliance delivers breakthrough for NZ business
The potential for better business performance by connecting Business Intelligence, Data Warehousing and Analytics has encouraged two technology companies to form a new strategic alliance for the New Zealand market. Business Intelligence company Mindfull has teamed up with Data Warehousing and Big Data specialist firm WhereScape to provide integrated and automated solutions to Big Data collection, management and analysis. Mindfull Director, Richard Johnson, said Mindfull and WhereScape offered complementary expertise which, when combined, would provide businesses with a powerful toolkit to boost performance.
“Our expertise in Business Intelligence partnered with WhereScape’s expertise in Data Warehouse Automation makes for a compelling proposition and fills a large gap in Big Data services. Most modern, enterprise-level businesses understand how big data can have an impact on performance. But all too often they’ve struggled to make the data work for them, usually because they’ve found the whole process time-consuming, costly and technically difficult. Our alliance with WhereScape allows us to offer our customers an integrated and automated solution where data can be gathered, interpreted and presented in a way that allows businesses to gain the insights they need to improve performance.”
WhereScape Vice President Asia Pacific, David Morris, said the alliance with Mindfull, WhereScape’s only ‘platinum partner’ in New Zealand, was a giant step forward in the Big Data revolution in the region. It will bring new ammunition to the data wars, with smart companies using data as their secret weapon. Increasingly, companies are being asked to do much, much more with much less, but do it far more quickly, he said. Rallying armies of data to inform business manoeuvres not only reduces risk but can provide a strategic advantage if you have more information than your opponents.” Morris points out the pitfalls obstructing data hungry companies in making fast decisions; large teams, projects that take too long and deliver little, budget cuts and decreased resources and time spent maintaining what is already built.
“There were common themes from discussions that we’ve had with executives – organisations were juggling too many projects with tight timeframes. So together with Mindfull we set out to do something about it. The result is a partnership that combines business intelligence analytics with data warehouse automation to gain efficiencies and effectiveness. For example, WhereScape’s automated solutions eliminate time-consuming, repetitive tasks such as coding.”
“Together we are able to get solutions up and running – and deliver results – in days and weeks rather than months and years, as well as providing businesses with an ability to respond rapidly to changing needs and conditions. The secret to success is to learn how to do more with less” concluded Morris.
What Makes A Really Great Data Model: Essential Criteria And Best Practices
By 2025, over 75% of data models will integrate AI—transforming the way businesses operate. But here's the catch: only those with robust, well-designed data models will reap the benefits. Is your data model ready for the AI revolution?Understanding what makes a great...
Guide to Data Quality: Ensuring Accuracy and Consistency in Your Organization
Why Data Quality Matters Data is only as useful as it is accurate and complete. No matter how many analysis models and data review routines you put into place, your organization can’t truly make data-driven decisions without accurate, relevant, complete, and...
Common Data Quality Challenges and How to Overcome Them
The Importance of Maintaining Data Quality Improving data quality is a top priority for many forward-thinking organizations, and for good reason. Any company making decisions based on data should also invest time and resources into ensuring high data quality. Data...
What is a Cloud Data Warehouse?
As organizations increasingly turn to data-driven decision-making, the demand for cloud data warehouses continues to rise. The cloud data warehouse market is projected to grow significantly, reaching $10.42 billion by 2026 with a compound annual growth rate (CAGR) of...
Developers’ Best Friend: WhereScape Saves Countless Hours
Development teams often struggle with an imbalance between building new features and maintaining existing code. According to studies, up to 75% of a developer's time is spent debugging and fixing code, much of it due to manual processes. This results in 620 million...
Mastering Data Vault Modeling: Architecture, Best Practices, and Essential Tools
What is Data Vault Modeling? To effectively manage large-scale and complex data environments, many data teams turn to Data Vault modeling. This technique provides a highly scalable and flexible architecture that can easily adapt to the growing and changing needs of an...
Scaling Data Warehouses in Education: Strategies for Managing Growing Data Demand
Approximately 74% of educational leaders report that data-driven decision-making enhances institutional performance and helps achieve academic goals. [1] Pinpointing effective data management strategies in education can make a profound impact on learning...
Future-Proofing Manufacturing IT with WhereScape: Driving Efficiency and Innovation
Manufacturing IT strives to conserve resources and add efficiency through the strategic use of data and technology solutions. Toward that end, manufacturing IT teams can drive efficiency and innovation by selecting top tools for data-driven manufacturing and...
The Competitive Advantages of WhereScape
After nearly a quarter-century in the data automation field, WhereScape has established itself as a leader by offering unparalleled capabilities that surpass its competitors. Today we’ll dive into the advantages of WhereScape and highlight why it is the premier data...
Data Management In Healthcare: Streamlining Operations for Improved Care
Appropriate and efficient data management in healthcare plays a large role in staff bandwidth, patient experience, and health outcomes. Healthcare teams require access to patient records and treatment history in order to properly perform their jobs. Operationally,...
Related Content
What Makes A Really Great Data Model: Essential Criteria And Best Practices
By 2025, over 75% of data models will integrate AI—transforming the way businesses operate. But here's the catch: only those with robust, well-designed data models will reap the benefits. Is your data model ready for the AI revolution?Understanding what makes a great...
Guide to Data Quality: Ensuring Accuracy and Consistency in Your Organization
Why Data Quality Matters Data is only as useful as it is accurate and complete. No matter how many analysis models and data review routines you put into place, your organization can’t truly make data-driven decisions without accurate, relevant, complete, and...
Common Data Quality Challenges and How to Overcome Them
The Importance of Maintaining Data Quality Improving data quality is a top priority for many forward-thinking organizations, and for good reason. Any company making decisions based on data should also invest time and resources into ensuring high data quality. Data...
What is a Cloud Data Warehouse?
A cloud data warehouse is an advanced database service managed and hosted over the internet.