Our Analytics practice provides consultancy services enabling customers to transform their business through innovation, insight and analytics. Our core philosophy is to build on our successful delivery in the areas of Finance, Pharmaceutical, Manufacturing and Telecommunications, to find the best solution for our customers and to unlock strategic value from their organisations data. Our approach is simply to put the customer first, to understand them and to engage in an agile, collaborative process that is focused on providing value.
As a boutique international consultancy services company, we are business focused and agnostic from a technology perspective. We believe in having an impact and have assisted customers across various domains in transitioning from using their data in a reactive manner, to proactively using data as an asset to service their customers and grow their organisations.
We have a successful history of delivering innovative data solutions for customer on subjects including business intelligence, analytics, big data and information architecture. Our projects range from departmental point solutions to global implementations for large scale enterprises.
Whether our customers are starting their project journey or wish to evaluate an existing implementation, we have a suite of strategic services to enable organisations expedite that journey.
By leveraging the knowledge, experience and best practices from our previous engagements, our consultants have a proven methodology to support customers in taking an idea or business focus and developing it through to a tangible roadmap, which typically includes a customised combination of the following services:
- Strategy Mapping
- Master Data Services
- Data Strategy
- Metric and KPI definition
- Solution architecture design
- Investment recommendations
- Budget, costing and licensing
There are several different definitions of Business Intelligence. However, at its root, BI is simply the gathering and organising of data for access, analysis and exploration.
BI supports the organisation to:
- Transform data into information
- Information into insight
- Insight into decisions and actions
Our Business Intelligence team has a mixture of both IT skills and business performance improvement expertise to ensure BI solutions are designed to provide tangible results and maximise return on investment.
Our team of BI consultants can offer support at any of the 3 key stages of the Business Intelligence project. So whether you are starting your BI project or require support and expertise to execute a current project, DNM has the skills and experience to support you on your BI journey.
Most successful Business Intelligence implementations provide the end users with the applications and tools to support the business in answering key questions, primarily focused on the “What happened?”
With the successful roll out of dashboards with drill down and trending capabilities, a new culture has ensued, in which people in organisations are moving from using their data to ask ‘What happened’ to ‘Why it happened’ and ‘What would happen if…?’ The move to these more improvement oriented questions shows the maturity growth of an organisation, and requires more advanced analytical tools and techniques to aid in achieving their business objectives and ultimately improve performance.
To support this organisational maturity, DNM have invested heavily in our Analytics capabilities. Our team of data scientists, Lean Six Sigma consultants and business analysts partner with our customers to design next generation Analytics solutions including key industry trends such as:
- Self-service analytics
- Data discovery
- Data visualisation
- Predictive analytics
- Customer analytics
AWS Data and Analytics
The amount of data we produce every day is truly mind-boggling. There are 2.5 quintillion bytes of data created each day at our current pace, but that pace is only accelerating with the growth of the Internet of Things (IoT). Over the last two years alone 90 percent of the data in the world was generated. Not surprising since more than 3.7 billion humans use the internet (that’s a growth rate of 7.5 percent over 2016). With about 456,000 tweets are sent on twitter every minute
The size and complexity of the data that needs to be analysed today, means the same technology and approaches that worked in the past, may not work anymore. To get the most value from your data, DNM in conjunction with AWS can provide you with a comprehensive, secure, scalable, and cost-effective portfolio of services that enables you to build your data lake in the cloud, analyse all of your data, including data from IoT devices with a variety of analytical approaches including machine learning.
Working with AWS services and using best practices in Business Intelligence and Data Warehousing, we have several customers with whom we have worked with to move, store and analyse their data. AWS services can be broken downs as follows:
The first step to building data lakes on AWS is to move data to the cloud. The physical limitations of bandwidth and transfer speeds restrict the ability to move data without major disruption, high costs, and time. As part of our data movement and data integration services, DNM have worked with AWS services to make data transfer easy and flexible, providing solutions for on-premise data movements or real-time data movement using AWS Snowball, AWS storage Gateway, or Amazon Kinesis data firehose.
Once data is ready for the cloud, AWS makes it easy to store data in any format, securely, and at massive scale with Amazon S3 and Amazon Glacier. To make it easy for end users to discover the relevant data to use in their analysis, AWS Glue automatically creates a single catalogue that is searchable, and query-able by users.
There are a number of storage solutions available from AWS which enable our customers to store their data in a secure, scalable storage based with what up to millisecond latency for data access. Using AWS Glue our customers can have a fully managed service that provides a data catalogue to make data in the data lake discoverable, and has the ability to do extract, transform, and load (ETL) to prepare data for analysis
AWS provides a broad range of cost-effective analytic services that run on the data lake. Unlike your traditional approach each analytic service is purpose-built for a wide range of analytics use cases such as interactive analysis, big data processing using Hadoop and Spark, data warehousing, real-time analytics, operational analytics, dashboards, and visualisations.
As Data Architects, DNM will understand your data model and hierarchy and help you map the right AWS service to your business requirements.
- Interactive Analytics – point and click, we use Amazon Athena to enable our customers to start querying their data instantly.
- Bid Data Processing – For big data processing using the Hadoop and Spark frameworks Amazon EMR provides a managed service that makes it easy, fast and cost-effective to process vast amounts data.
- Data warehousing – For data warehousing, Amazon Redshift provides the ability to run complex, analytic queries against petabytes of structured data, and includes Redshift Spectrum that runs SQL queries directly against Exabytes of structured or unstructured data in S3 without the need for unnecessary data movement.
- Real Time Analytics – For real-time analytics, we use Amazon Kinesis which makes it easy to collect, process and analyse streaming data such as IoT telemetry data, application logs, and website clickstreams.
- Operational Analytics – For operational analytics such as application monitoring, log analytics and clickstream analytics, we use Amazon Elasticsearch Service which allows you to search, explore, filter, aggregate, and visualise your data in near real-time.
- Dashboards and Visualisations – For quick dashboards and visualisations, we use Amazon QuickSight which provides you a fast, cloud-powered business analytics service, that makes it easy to build stunning visualisations and rich dashboards that can be accessed from any browser or mobile device.
Machine Learning – For predictive analytics use cases, AWS provides a broad set of machine learning services, and tools that run on your data lake on AWS. Our services come from the knowledge and capability we’ve built up as part of our AWS Next Generation Managed Services for our customers. Our 24/7 monitoring takes advantage of the latest statistical mechanisms and machine learning to provide a premium service. We are able to identify abnormal patterns of behaviour quickly and take the appropriate action, thanks to our heterogeneous monitoring. Given the dynamic and highly automated nature of AWS workloads, AWS services enable us to have visibility of the whole environment including application performance that scale instantly to adjust to changes in workloads being monitored.