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Project delivery
Data analysis
Systematic and repeated profiling of large datasets can be prone to human error and can be extremely labour intensive. Whether in preparation for new project implementations, or part of business-as-usual activity, Kagool can help your organisation to profile datasets across disparate IT landscape systems, consolidate the results, and provide relevant and accurate reports on status to
give you actionable strategic insight.
Having extensive experience delivering projects involving over 30 IT systems and over 500 business data rules across data volumes that exceed ten billion records, we have highly efficient industrialised solutions that can consume and profile huge data volumes, measure data quality and root out error states to teams for remediation and correction.
Our error states reporting solutions give you online, metric-driven and detailed accounts of your aggregated data, and enable you to drill right down to the heart of your data quality issues to solve or override them at source, directly from one of our online solutions.
Data migration and integration
Our transparent and tested migration and integration processes have been proven in the world’s most challenging industries.
Data is an increasingly integral component affecting your organisation’s bottom line: modern competitive organisations rely on data to automate processes and to drive efficiency.
Whether it’s the automated augmentation of customer profiles, or managing complex vendor relationships in your global manufacturing supply chain, your data offers its own intrinsic value as well as extrinsic risk to profitability should your data be managed incorrectly. Migrating your data from legacy systems or integrating new systems into your existing data landscape can therefore have an immediate effect on your business. It is still surprising how many organisations underestimate the impact of these activities until it all goes wrong.
We at Kagool have developed proven and robust systems for migrating and integrating datasets across a vast array of IT platforms and landscapes.
Our transparent and visible approach ensures that your business can monitor and track migration and integration activities, so that your transitions are assured and safe.
Kagool are also proven at rescuing and returning ownership of distressed data work streams from existing Systems Integration Partners, putting your business firmly back in control of your migration activities.
Kagool is recognised in the industry for high levels of diligence, governance, accuracy and customer satisfaction in Data Migration and Integration solutions.
Our proven approach ensures that:
- The end to end process is clear, transparent and visible to all
- All data validations are reported and actionable processes are integral to the process
- All loaded data should be reconciled against what was sent
- A separate end-point reconciliation process should run in parallel to ensure that the source and target systems remain in continuous alignment across the IT landscape
Kagool has developed a master data end-point reconciliation solution that ensures the integrity of master data across complex IT landscapes ensuring pro-active error reporting and remediation of master data interface failures, preventing costly reactive approaches when transactional data failures occur.
Dashboard analytics
We provide dashboards that give you strategic value.
Making sense of your raw business data, transforming this data into information with functional utility, and then using this information to provide actionable insight is a major challenge for all organisations.
What questions should you ask of your data? How do you extrapolate behavioural trends from your data? What predictive data will help to indicate, diagnose and remedy problems in your processes even before they occur? How can you exploit your data for advantage over your competitors?
Dashboards come in many shapes and sizes: Qlikview, Tableau, APEX, to name but a few. Many consultancies can create dashboards containing graphs, pie charts, clickthrough's and drill-downs, but these dashboards quickly become redundant if they can’t provide strategic value behind the visual layer.
Kagool has vast cross-sector experience providing data-driven dashboarding solutions from poorly utilised existing landscape datasets, helping companies gain competitive advantage through expert data and behavioural consultancy.
Our solutions are strategy-driven, and are a result of rigorous collaborative relationships with clients to understand their business processes, challenges and aspirations, in order to create end dashboards that provide answers to the questions that many businesses didn’t know they needed to ask.
MDM implementation
As your business continually generates data, without robust data governance techniques, your data is prone to inaccuracy and deterioration. Whether your business relies on accurate data for business-as-usual processes, or for predictive or strategic analysis, any degradation in the quality of your data will also ultimately lead to the degradation of your organisational effectiveness.
It is surprisingly common for simple master data errors in complex customised ERP environments to result in a cessation in transactional processing that often goes unnoticed until the problem manifests itself in the physical world, for example when your production line stops. This is why we at Kagool view MDM solutions, not as a system where master data is simply created and stored, but as a comprehensive system of enterprise data integrity measurements that continuously verifies that your master data is doing what it is expected to do.
We can help you to:
- Establish best-practice driven organisation governance models including roles and responsibilities for managing your data
- Model your business processes to manage your data, and provide guidance on implementing an effective IT solution
- Create and enforce standards for your data so that your data stays unified, consistent, precise and reliable
- Track, remediate and halt the proliferation of erroneous data
- Create data cleansing routines based on quality standards and your business rules.
- Provide these bespoke and ready-made robust IT solutions cost-effectively
Our consultants will work rigorously and collaboratively with you to understand your business processes in detail before designing solutions. Whether your business involves consumer MDM or product MDM, or your data is complex and stored over many different platforms, our proven experience working across many industries will mean that we can help you.
We can help with the implementation of a standard off the shelf MDM solution like SAP MDG or Oracle MDM.
However, if your business process is complex we can provide more flexible and bespoke MDM solutions that can support any complex workflow while satisfying the same control requirements.
Oracle Apex Development
Our APEX development team can deliver powerful and interactive mobile-enabled, cloud applications to allow your business users to take control of your business functions from anywhere, anytime.
APEX is a powerful visualisation and interaction layer that is packaged as part of the Oracle licensed installation. It provides a layer to support user interaction/input, graphical representation and personalised user experience. Applications can be developed and securely deployed using APEX in the same way that apps can be created and deployed in the digital marketplace.
Kagool has a relationship with Oracle to develop
industry leading applications to support multiple vertical markets. If you need cloud-based interactive access to your organisation’s data and functions, contact us to see how we can help.
Advanced data engineering services
Kagool’s Advanced Data Engineering Team provides specialist capabilities through Professional Services and also Build Factory models for the Microsoft Azure Platform. Covering everything from Ingestion, CDC, Analytics, Report Delivery, Automation, AI & Machine Learning - we have the qualified Data Engineering talent with extensive Manufacturing, Logistics & Supply Chain experience to help you accelerate leveraging Insights from your Landscape Big Datasets.
Data engineering involves the the design, development and management of information or "Big Data" IT landscapes. Data Engineers develop the architecture that helps analyse and process data in a way for the enterprise to generate meaningful actionable insights from it.
Data engineers are part of a larger organisational team which includes business and IT leaders, middle management and front-line employees. The goal is to leverage both internal and external data - as well as structured and unstructured data - to gain competitive advantage and make better business decisions.
Data Engineers manage the operational tasks to support the following activities critical for analytics including: Data Ingestion, Data Synchronization (CDC), Data Transformation, Data Models, Data Governance, Performance Optimization, Production Orchestration.
Ingestion
This is the task of getting data out of source systems and ingesting it into a data lake. A data engineer would need to know how to efficiently extract the data from a source, including multiple approaches for both batch and real time extraction as well as needing to know about both standard connections like JDBC as well as high-speed proprietary connections like TPT. They would need to know about how to deal with issues around incremental data loading, fitting within small source windows and parallelisation of loading data as well for performance consideration.
Synchronisation
This could be considered a subtask of Data Ingestion, but because it is such a big issue in the big data world since hadoop and other big data platforms don’t support incremental loading of data, it is listed it separately. Here the data engineer would need to know how to deal with how to detect changes in source data (CDC), merge and sync changed data from sources into a big data environment. Kagool offers a solution for this called Velocity.
Transformation
The "T" in ETL and focuses on integrating and transforming data for specific use cases. The primary skillset is knowledge of SQL and may involve other technologies also such as Python.
Governance
Data engineers are not responsible for the governance of the data, they do however need to ensure the systems that are needed for data access control and data lineage, are put in place and support the capabilities that are required for good data governance. When a data engineer implements a solution for data ingestions, sync, transformation and models, they need to be aware of data governance concepts so the tooling and platform also support the need for good governance.
Performance Optimisation
Anyone can build poorly performing systems, the challenge is to build data pipelines that are scalable and efficient.
So the ability and understanding of how to optimise the performance of an individual data pipeline and the overall system are a higher level data engineering skill. For example, big data platforms continue to be challenging with regard to query performance and have added complexity to a data engineer’s job. In order to optimise performance of queries and the creation of reports and interactive dashboards, the data engineer needs to know how to de-normalise, partition, index data models, or understand tools and concepts regarding in-memory models and OLAP cubes.
Production Orchestration
It is one task to build a data pipeline that can run in an
experimental sandbox. It is a second, to get that to perform optimally. It is yet another skill to build a system that allows you to rapidly promote data pipelines from prototype to production, monitor the health and performance of those pipelines and ensure fault tolerance of the entire operational environment. Like performance optimisation, this requires a higher level skill that you tend to see in much more senior data engineers.