Business Intelligence & Data Analytics
Data Engineering
SERVICE OFFERINGS
Inspur not only builds powerful predictive analytics software solutions, we also help organizations develop and implement data strategies, put the necessary technical tools in place and optimize the data analytics environment to help you drive tangible results.
Two major data engineering services we are offering, get the details:
The ever-growing volume of data that organizations have at their disposal presents a series of daunting challenges.
-
Determining which data to collect, and having a sound rationale for doing so
-
Establishing methodologies for efficiently accessing, classifying, assessing and prioritizing data
-
Rapidly deploying analytical models for business users to incorporate into routine business operations
-
De-mystifying and simplifying analytics for business users
-
Deriving business insight from the data
-
Effectively monetizing business insight
-
Institutionalizing an analytics culture and associated behaviors among business users
-
Managing the ongoing storage and computing requirements associated with the ever-growing volume of data
In most organizations, a relatively small cadre of data science professionals is responsible for big data analytics. This team typically manages a gargantuan set of related tasks:
-
Developing analytical models
-
Testing model accuracy
-
Deploying models effectively into the business
-
Collaborating with the IT organization to facilitate model deployment
-
Coaching business users on using analytical tools
-
Maintaining analytical models so that they retain their accuracy
​
These activities comprise a never-ending cycle that can exhaust even the most coffee-dependent, fanatical data scientist. Hiring more data scientists can help alleviate some of the pressure, but these skills are scarce in the marketplace. Beyond that, there are still only 24 hours in a day.
Data Analytic Assessment
Your data can help you see into the future, and predictive analytics hold the key for unlocking that forward-looking capability.
​
Imagine that you have an advanced capability to learn from historical predictive analytics. You develop decision algorithms and implement automated versions of these to make your business processes more agile. As your data warehouse grows to contain ever more data, your algorithms refine their predictive capabilities, becoming increasingly accurate and adapting to changing data patterns to retain their predictive accuracy over time. Business leaders within your organization marvel at their ability to generate tangible and accurate insights and apply this knowledge to make timely, informed decisions that drive results.
​
Inspur can help make that happen for your organization.
​
Our team of data scientists collaborates with you to quickly develop a comprehensive assessment of your organization’s data assets and capabilities, related operational processes and supporting technical environment, as well as the potential value that an optimized data strategy, operations playbook and systems architecture can deliver.
​
Over the course of several weeks, Inspur will assess key aspects of your big data analytics environment, such as:
​
-
Data inventory: How extensive is your data repository and where is data stored?
-
Accessibility: How does your organization access data, and how efficient is this?
-
Data quality: To what extent must your team modify or “clean” data before it can be used? Do your current systems populate critical data elements at all times?
-
Coverage: To what degree do your current analytical processes deliver results that accurately map to business processes and decisions?
-
Accuracy: How accurate are your predicted results, both initially and over time, after you have deployed predictive models to business users in your organization? What possible actions could improve accuracy?
-
Automation: To what degree is the process for “operationalizing” predictive models automated? What options are available to enhance automation to accelerate deployment of predictive models and model updates to business users?
​
As the Inspur team works through these and other topics with you, we develop an assessment that is customized to your organization. You’ll receive both strategic and tactical recommendations, spanning data strategy, operational processes and technology enablers, all reflecting your organization’s unique requirements and technological capabilities. With this assessment in hand, you’ll be much closer to the goal of seeing accurately into the future.
Predictive Data Modeling
Translating years of data into helpful automated decisions requires a consolidated analytics approach. Doing so also requires a keen understanding of how to separate critical data from “data noise” and use the critical data to deliver insights that you can apply to drive business decisions. Predictive models can unlock the hidden value of your data if they are structured properly and draw the subset of relevant data from the larger set of data that your organization administers.
​
Inspur can build predictive models that optimize your data assets.
​
We start with an experienced team of data scientists. Our team consists of senior information technology and data science experts. All have advanced degrees and extensive experience in predictive analytics, software integration and business process optimization.
​
By mining your data, our scientists are able to assess its predictive power. Depending on the quality and coverage of your data, you can use it to improve business results dramatically and rapidly. Some benefits that we’ve observed:
​
-
Stronger revenue growth through more precisely targeted activities
-
Lower business risk by identifying and proactively reducing risk profile
-
Greater profitability by generating revenue growth with either the same or a lower cost structure
​
Our team will uncover data patterns hidden in the tables, rows and columns where your data lives. We will convert this data into predictive models that invalidate subjective preconceptions, affirm other hypotheses and reveal entirely new insights. We’ll also offer you recommendations about how to integrate your data models into a comprehensive data strategy.
​
Once we do so, we turn over the models to you, and you will be ready to start benefiting from more robust analytics that support a more consistent predictive analytics strategy.