Data & Advanced Analytics as a Service

Customer data and analytics are critical to driving the business forward. The platforms and tools available can make all the difference in how one approaches this task. At Axacraft, we help in understanding what capabilities are most important for business success and then selecting the best approach for achieving them to create a seamless customer experience that increases customer loyalty.

Data & Advanced Analytics as a Service
Some of the most successful companies are those that have embraced data-driven decision-making.
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Some of the most successful companies are those that have embraced data-driven decision-making.

Basing business decisions on real, tangible data brings many benefits, including the ability to spot trends, challenges, and opportunities before your competition.

As your organization grows, it becomes increasingly important to have employees whose job is specifically anchored around data.
Grasping the data opportunity

As your organization grows, it becomes increasingly important to have employees whose job is specifically anchored around data. We can help establish the technical and capabilities foundation for a successful data and analytics team.

Axacraft has seen many companies start their analytics journey eagerly, but without a clear strategy.“intellectual curiosity” rather than a serious effort to change the business. Democratization of data is blurring sector boundaries; businesses will increasingly find themselves disrupted not by the company they have been monitoring for the last several years, but by a newcomer from another industry.

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Making sense of data science & analytics team structures.

Many of our clients are versed in gathering and interpreting data to some extent. As their organization grows, however, it becomes increasingly important to have employees whose job is specifically anchored around data. Axacraft provides the capabilities and structure to work side-by-side with an organization so that their culture becomes one rooted in savvy data practices.

Making sense of data science & analytics team structures.s and employees demand.
We bring (and train) key players to the data team.
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We bring (and train) key players to the data team.

While team structure depends on an organization’s size and how it leverages data, most data teams consist of three primary roles. Axacraft supplements client teams with data scientists, data engineers, and data analysts. Other advanced positions, such as management and data governance are often part of our client projects.

Data Science

Data science is the process of building, cleaning, and structuring datasets to analyze and extract meaning. When designed correctly and tested thoroughly, algorithms can catch information or trends that humans miss. 

Data Analytics

Data analytics, on the other hand, refers to the process and practice of analyzing data to answer questions, extract insights, and identify trends. The main goal of business analytics is to extract meaningful insights from data that an organization can use to inform its strategy and, ultimately, reach its objectives. 

Data Science

Gain customer insights to reveal details about habits, demographics, preferences, and aspirations.

Axacraft can supplement experience teams or provide a foundational understanding of data science which can help make sense data and how to leverage it to improve user experiences and inform retargeting efforts.

  • Increase security:

    Use data science to increase your business’s security and protect sensitive information. For example, machine-learning algorithms can detect bank fraud faster and with greater accuracy than humans, simply because of the sheer volume of data generated every day. 

  • Inform internal finances:

    Your organization’s financial team can utilize data science to create reports, generate forecasts, and analyze financial trends. Data on a company’s cash flows, assets, and debts is constantly gathered, which financial analysts use to manually or algorithmically detect trends in financial growth or decline.

  • Streamline manufacturing:

    Manufacturing machines gather data from production processes at high volumes. In cases where the volume of data collected is too high for a human to manually analyze it, an algorithm can be written to clean, sort, and interpret it quickly and accurately to gather insights that drive cost-saving improvements.

  • Predict future market trends:

    Collecting and analyzing data on a larger scale can enable you to identify emerging trends in your market. By staying up to date on the behaviors of your target market, you can make business decisions that allow you to get ahead of the curve.

Data Analytics

Analytics is used to extract meaningful insights from data that can drive decision-making and strategy formulation.

Budgeting and forecasting

By assessing a company’s historical revenue, sales, and costs data alongside its goals for future growth, an analyst can identify the budget and investments required to make those goals a reality.

Risk management

By understanding the likelihood of certain business risks occurring—and their associated expenses—an analyst can make cost-effective recommendations to help mitigate them.

Marketing and sales

By understanding key metrics, such as leadto- customer conversion rate, a marketing analyst can identify the number of leads their efforts must generate to fill the sales pipeline.

Product development

By understanding how customers reacted to product features in the past, an analyst can help guide product development, design, and user experience in the future.

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Analytics is used to extract meaningful insights from data that can drive decision-making and strategy formulation.
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Excel in data science for business & gain a competitive advantage.

New to data science? Axacraft can help your enterprise gain a foundational understanding of data science and how it relates to organizational success. Additionally, we can create a data-driven framework for your organization and help your teams understand key techniques. If your teams are experienced already, we can offer high-performance teams even more capability.

Excel in data science for business & gain a competitive advantage.