What is Big Data?
Big Data might seem like a new buzz word, something that has only recently come about. In reality the act of gathering and storing large amounts of information for eventual analysis is an old practice that has been digitised in recent years.
However, there are at least two key difference from traditional data storage:
- Data first – where the goal is often to capture the raw data in unstructured formats, so that it can be analysed afterwards. This is often the opposite requirements driven process used in traditional relational SQL databases.
- The volume of the data captured can scale beyond traditional data stores.
Large volumes of data inundates businesses on a daily basis. Raw data is useless unless some analysis is applied to extract relevant business information and this is where Big Data comes in. The pivotal role that Big Data plays is in the way insights and main points of focus are gathered from this large volume of data and presented to the business in a format that helps optimize decision making within the organisation.
Mining for Gold in Data – Key Uses Cases
As an integration provider we integrate a number of different “Big Data” technologies to provide organizations insight and data driven decision making tools:
- Elasticsearch (now just elastic.co) – an early unstructured data store with powerful search engine. With Auto scaling and clustering elastic search has also become a tool for capturing log data including access logs, trading data for large banks to retail and manufacturing log data. The ability to ingest, monitor trends on dashboard with Elastic Kibana and search has made the open source elastic stack as one of our most popular tools for data insight in both operations, retail and security domains.
- For organizations willing to be Json centric the simplicity and scaling of MongoDb is hard to beat. A single engine is able to drive both web, mobile and data capture across the whole organizations.
- When there is a need for speed the MapR high performance key value is an increasingly popular integration and the sql like Spark querying has increased the commonality and made Big Data adoption easier.
Liberate Not Liquidate
Due to the complications of handling, categorising and organising data manually this privilege was mostly reserved to large entities. Nowadays with the advancement of technology it is possible for any person to aggregate and gain access to the right data in order to make informed decisions. This information is easily attained, cheaply recorded and maintained (consumers pay by use for cloud computing and SAAS Big Data management).
While the nearly all Big Data vendors will naturally claim to be the best choice for the next generation enterprise, we believe in best of breed and agility rather than silver bullet solutions. As a result Ricston have developed an agile open source Mule ESB backbone solutions that allow the adoption of Big Data tools while maintaining the investment in relational (e.g. Oracle) and traditional business and reporting tools ( e.g SAP).
And with the variety of cloud connectors enterprises can often trial and adopt cloud based implementations rapidly while maintaining a managed gateway of security and data.
How do we overcome challenges to make better use of Big Data?
Big Data challenges can be categorised and analyzed further by describing the 3 Vs
As technology advanced, it became possible to store huge amounts of data in small spaces. Hence organizations have the ability to gather unfiltered raw information from multiple sources, including business systems, legacy or SAAS, transactions, social media interaction and information from sensor or other machine generated data.
With the expectation of real time interaction and push of a button information, data moves from one endpoint to another at an unprecedented speed and is processed or transformed to help categorise and give the required search feedback or reports. RFID tags, sensor GPS, and networks of any sort are constantly feeding software ecosystems. Often organizations do not only need to rely on their own data but they can leverage third party data which does not even need to be stored on their own setup.
Data comes in all shapes and sizes, formats of information varies from structured, numeric data in traditional databases to unstructured text documents, email, conversation threads, audio/videos etc. Integration standardisation and data transformation play an integral part to ensure that data is interpreted, valued and used to offer human readable patterns, ’cause and effect’ lessons and other feedback that help improve systems, procedures, workflows, efficiency and productivity.
Data which cannot be interpreted and used to one’s advantage is quite mundane and seen as small clutter, but when everything is linked together and fused across multiple data sources, this same data becomes useful information. When put into perspective it translates into Big Data giving you valuable insights that can be used to address critical challenges.
Connected Enterprise is a Key to utilising, managing and securing Big Data
To manage ‘Big Data’ you need the data to be transparent and accountable to help identify areas of process and performance improvements. Ricston can help you merge data from different sources and devices, visualise and analyse it in real time. The main technology that we work with is Anypoint Platform with its core – Mule ESB that offers limitless opportunities to transform your business through IT.
In a world that continues to become more and more open and connected, businesses also have to consume data that is not created internally, but acquired through various sources such as partners, customers and other third parties. With the increase in data sources and innovative enterprise solutions, Point to Point systems don’t work anymore. With Anypoint Platform it is not only possible to integrate software and systems, but also easily build open API’s on top of your business systems to give secure and regulated access to your data, algorithms, or applications for third parties.
Security has grown to become one of the paramount areas in IT – customer’s private information (could be medical or financial) is prone to security breaches by hackers. This is why your data safety is of vital importance and we at Ricston take this security very seriously. Mule ESB sits in the middle of multiple systems, channelling and transforming data between one system and another. In most cases data between SAS systems is exposed via APIs. Using these APIs, Ricston can govern different security rights for different groups of users. For example an IT person working on internal APIs would have wider access and manipulation capabilities when compared with third party partners. By implementing this kind of setup, Ricston can protect your data whilst still promoting cooperation through the use of user authentication and encryption techniques.