Big Data, Cloud & DevOps

Companies are increasingly leaning towards well-governed, self-service BI models that combine the necessary speed and flexibility. Both the self-service model and governed models are distinct entities. In the self-service model, the organization gets direct access to complex technical tools and datasets on-premise. They use these tools to extract data, creating reports and gleaning information from them. With the governed model, the data is fed to an IT team where they construct data pipelines from the data source and put it all into a central data warehouse.

While DevOps implemented using the Total DevOps approach provides a strong foundation for long-term enterprise business improvements, it is important to understand DevOps is not an island. Enterprises implementing DevOps should be aware that DevOps interoperates with other IT systems and practices. Enterprises are well-advised to choose tool-agnostic IT partners that can provide solutions that best suit the needs of each unique enterprise and can integrate and evolve DevOps together with all their IT systems.

Project management is a relatively new profession, there is no consistent picture of what a project manager is, and what competencies individuals filling a project management role should have. There are no one-size-fits-all competencies required for operational project management (OPM) in today’s era of digital disruption. Nevertheless, there are certain important behavioural and personal competencies that should always be taken into consideration when appointing a new project manager, or looking at the competencies an already-employed project manager would require in order advancing his or her career prospects.

If you know some SQL, I hope you find this article useful as well and see some other things might add to your knowledge. You can mostly write queries with SQL. This is almost right because SQL is very intuitive. In this tutorial, you will learn how to create a table, insert values into it, use and understand some data types, use SELECT statements, UPDATE records, use some aggregate functions and more.

There are many nuances in creating a data science team that taking it loosely will certainly lead into failure. So far, it should be clear how different technical roles and expertise along with soft skills intertwine to create a team that can achieve great objectives in data science. Selecting individuals to join such a team is a great challenge and needs to be done with care. Here are huge opportunities for data scientists to interact and learn from each other. 

Information extraction is a major problem in the fields of natural language processing and web mining, in particular when it comes to evaluating domains where language cannot be taken at face value. In modern artificial intelligence (AI) community, information extraction is done using machine learning. Supervised machine learning methods take training set of webpages, with gold standard extractions, and learn an IE function based on statistical models like conditional random fields and even deep neural nets.

Value based prioritisation should be at the centre of any organisation and form the building block of any agile methodology. Companies that prioritise their strategy by value adapt quicker and work iteratively to continuously deliver a more valuable product to their customer, and at a much faster rate than their competitors. Working this way ensures that every team member is directing their energies for the same goal to unlock the full potential of the business.

There is no magical technology platform or service provider which can be – on its own – the answer to a fundamental transformative challenge around cyber security. The overarching challenge for the CISO lies in getting senior management to see that long-term change is rooted in a long-term vision and long-term planning which takes time to establish. Simply throwing money at the problem in the hope of making it disappear, without a proper consideration of those matters simply leads to failure and can only aggravate the perception by senior stakeholders that security is just a cost and a burden.

By helping surface information, visualization tools create a bridge between graph data and viewers. Graph libraries are an important layer of the graph technology landscape. They let you build custom visualization application for network data and you can pick from a large catalog depending on your favorite language, license requirement, budget or project needs. These are mainly JavaScript libraries but you’ll also find other languages. This post lists libraries of various ‘depth’, some offering basic layouts and interaction, other more advanced customization and integration options.

When done well, DevOps can remove inefficiencies by improving process and performance but only when clear outcomes are established. These improvements are transferable across a wide range of industries, with consistent benefits achievable for organisations of all sizes. So if you are looking for reasons why you should introduce DevOps,here are five benefits that  help you make that decision. However, these benefits are all intrinsically linked, so there’s little chance that all will immediately appear once your DevOps journey has begun. 

DevOps has come a long way in the last 10 years. From its humble beginnings, the mash-up between development and operations has grown into a major focus for businesses all over the world. Today, more than 70 per cent of companies claim to have adopted DevOps, and it’s easy to see why. Sadly, most organisations are failing to hit numbers. Here’s five key ways businesses are still getting it wrong – and what they can do about it.