Tag: data

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Business Intelligence
08 avril 20190

Did You Know?? Real-time Intelligence = Value

Do you know how easily your organization’s business intelligence can turn into a lost opportunity? Well, it is just a matter of TIME. Intelligence is of value if, and only if it arrives on time.

In today’s hyper-competitive market environment, business intelligence continues to be an area of investment and interest for businesses. The ability to turn raw data into meaningful and useful information that can impact business performance is a powerful value proposition.

Despite the emergence of new devices and software products designed to unite employees in more ways than ever before, the threat of organizational silos is still very real.

Lack of collaboration between individuals and teams in different departments working on similar assignments and projects could ultimately lead to inefficiencies and loss of productivity.

The best-case scenario for this duplication of data analysis is that teams come up with the same result. When individuals or teams produce different numbers this cause disagreements about who had analyzed the ‘correct’ data and which can be fully trusted.

In the grand scale of things, this distorted view of data can be devastating, but there are even more ways that data silos can put your business in danger.

Keeping a pulse on business’ sales, marketing, finances, web analytics, customer service, internal R&D, IT, and more as isolated sources of data will never give a complete picture.

The scary truth is big data doesn’t lead to big insights if you can’t bring it together.

Yet many businesses are only scratching the surface of what’s possible with business intelligence.

To realize the potential of business intelligence and take its value to the next level in your organization, you need a solid understanding of where you are, what you want to achieve, and what’s possible.

From generating reports and charts that depict business performance, to implementing a truly transformative solution that uses powerful advanced analytics to not only predict behaviors and outcomes but to prescribe  recommended courses of actions, business intelligence can be a strategic weapon that significantly impacts your bottom-line.

The next breakthroughs in business intelligence (BI) and analytics will see machine learning and artificial intelligence used to improve data access and data quality, uncover previously hidden insights, suggest analyses, deliver predictive analytics and suggest actions.

BI and analytics vendors are developing “smart” capabilities that will power the next step beyond self-service analytics, helping to further democratize data analysis for business users.

The benefits of business intelligence tools far outweigh the investments they entail. They can help businesses gain valuable insights to affect growth, resolve urgent concerns, collate marketing data more quickly, provide a real-time view of the organization and allow for the anticipation of future outcome using predictive and prescriptive analytics and forecasting.

Data Quality Management
21 novembre 20180

Dirty Data – Hygiene Etiquette

If you’ve ever analyzed data, you know the pain of digging into your data only to find that the data is poorly structured, full of inaccuracies, or just plain incomplete. But « dirty data » isn’t just a pain point for analysts; it can ultimately lead to missed opportunities and lost revenue to an organisation.  Gartner research shows that the “average financial impact of poor data quality on organizations is $9.7 million per year.”

The amount of time and energy it takes to go from disjointed data to actionable insights leads to inefficient ad-hoc analyses and declining trust in organizational data.

A recent Harvard Business Review study reports that people spend 80% of their time prepping data, and only 20% of their time analyzing it. And this statistic isn’t restricted to the role of the data stewards. Data prep tasks have bled into the work of analysts and even non-technical business users.

Enterprises are taking steps to overcome dirty data by establishing data hygiene etiquette:

  • Understand your data location, structure, and composition, along with granular details like field definitions.

Some people refer to this process as “data discovery” and it is a fundamental element of data    preparation. Confusion around data definitions, for example, can hinder analysis or worse, lead to inaccurate analyses across the company. For example, if someone wants to analyze customer data, they may find that a marketing team might have a different definition for the term“customer” than someone in finance.

  • Standardize data definitions across your company by creating a data dictionary.

This will help analysts understand how terms are used within each business application, showing the fields are relevant for analysis versus the ones that are strictly system-based. Developing a data dictionary is no small task. Data stewards and subject matter experts need to commit to ongoing iteration, checking in as requirements change. If a dictionary is out of date, it can actually do harm to your organization’s data strategy. Communication and ownership should be built into the process from the beginning to determine where the glossary should live and how often it should be updated and refined.

  • Data cleansing prior to imports

You need to prepare your data before even thinking of importing it in your system.  Every organization has specific needs and there is no ‘one size-fits-all’ approach to data preparation. A self-service data preparation tool allows people to see the full end-to-end process, seeing potential flags earlier on—like misspellings in the data, extra spaces, or incorrect join clauses. It also increases confidence in the final analysis.

  • Hands off!!

Keeping your hands out of the data in regular use increases the chances of it keeping clean. Introducing a little dirty data to a system will compromise an entire data set and your little bit of dirty data has suddenly created a lot of dirty data. Cleansing the mess is a far far bigger job than making sure the data is clean before importing it.

  • Invest in a self-service business intelligence tool

Adopting a self-service data prep across an organization requires users to learn the ins and outs of the data. Since this knowledge was historically reserved for IT and data engineering roles, it is crucial that analysts take time to learn about nuances within the data, including the granularity and any transformations that have been done to the data set. Scheduling regular check-ins or a standardized workflow for questions allows engineers to share the most up-to-date way to query and work with valid data, while empowering analysts to prepare data faster and with greater confidence.

Data hygiene should be a top concern in organisations. Devoting some resources to ensuring that the data you’re basing decisions on is complete and accurate is a smart investment, because dirty data is costly in so many ways. To get the most and best use out of your data, you need to take the time to ensure its quality is sufficient and that data used by different departments is integrated. This gives you the most complete and precise customer view, so you can make smarter decisions and maximize your return on investment.

Self-service Analytics
26 octobre 20180

Manage your Hospitality using Tableau Software

Data and analytics are playing an increasingly critical role in hotel and leisure operators’ understanding of their customers’ behaviour, so that swift actions can be taken to really satisfy their needs and wants.

At the same time, hotel operators have multiple datasets lying in various locations – customer profiles, customer feedback, occupancy rates, F&B sales etc. – creating data silos, from which the fullest potential cannot be tapped until they are integrated to gain a single version of truth.

Your teams could use Tableau to develop weekly and monthly reports that they could share with the entire company. The reports could feature sales figures and updates from top management and country managers, marketing and financial data, along with other growth updates. The comprehensive dashboards make sharing complex information with the rest of the company a much easier task.

With weekly reporting that details KPIs and shows how booking patterns are changing, details on revenue, commission and conversion rates but to name a few, allows you to extract the best insights for the team.

Tableau helps you stay competitive by making the time to develop and deliver insightful analysis and reports significantly shorter.

A business, which is highly metric-driven, is optimized with Tableau’s rapid-fire data analytics and drag-and-drop functions as period-on-period metric can be compared.

Tableau is a powerful tool because of its cross-platform adaptability. Tableau’s beautiful dashboards can be mobile-optimized, which makes it easy for everyone to access the findings even on the go. Tableau basically has the power to give you any insights you are looking for from the data that you can get your hands on.

Tableau can be a huge game-changer. So instead of having to wait for something to already happen and then try to figure out why it happened, you can now proactively look out and see what’s going to happen before it happens and then prepare for that or maybe change it.

 

Self-service Analytics
08 octobre 20180

My World 2030 – Harness data to drive sustainability and corporate responsibility

Over the past couple of months if not years we have seen headline grabbing scandals in various sectors of the economy worldwide.  The public trust is being hugely impacted with regards to the competence of executive leadership, integrity and transparency.

Earning trust requires the utmost attention to demonstrating ethical leadership, responsible (and responsive) business practices, transparency, and a genuine commitment to an organisation’s mission.

Companies are being encouraged to put their increased profit into programs that give back to society in terms of environmental, social, and governance (ESG) aspects More than ever before, there’s growing expectations that organisations will continue to play a very active role in solving social problems such as poverty or discrimination. It’s important that organisations set standards of ethical behaviour for its peers, competition and industry.

So how can data drive sustainability and corporate responsibility? The writing is on the wall!  With the rapidly evolving technology and high velocity and volume of data flooding organisations, it becomes imperative to provide users with an ultimate analytics experience, one with zero discernible latency when interacting with data. By giving users the right tools, they will explore avenues to use data to solve real world problems.

As data becomes more available and analytic literacy more pervasive, it is crucial that companies continue to focus on how their business operations are impacting the value chain, from the farm to the factory to the boardroom.

With the advent of sensors and devices in mobile objects, companies can now leverage spatial data for powerful geospatial analysis for environmental risk assessments. The better the data sets available to assess these risks, the more informed the decisions about adaptation are likely to be.

Energy and Resources give modern society its high standard of living and produce vast quantities of data, from the energy used to the resources needed to make many of these things that help us in business and our everyday lives.

Without a deep understanding that energy is finite and that energy transformations impact not just individuals but also the environment., companies and society at large won’t be able to make informed decisions about the future. With an efficient platform for gaining insights across geographies, products, services, and sectors, companies can maximize downstream profits and minimize upstream costs.

It is the era of data-driven environmental policy-making. Governments can now harness data to effective policy making. Data analytics and visualisation give the opportunity to make the invisible visible, the intangible tangible, and the complex manageable. A data driven government calls for strong leadership and investment. This is highly feasible.  A data driven government would make it easier to identify problems, track trends, highlight policy successes and failures, identify best practices, and optimize the gains from investments in environmental protection. A responsive government would work in close collaboration with businesses, NGOs and the academic community for more conscientious environmental decision-making.

Data alone will not help us achieve the UN SDGs. What we need is strong leadership both from businesses and governments, transparency , integrity and a genuine commitment to the UN 17 SDGs. These combined with modern data analytics will provide collaborative, multilateral solutions to global challenges.

This is My World 2030!!

Data Governance, Data Regulations
25 septembre 20180

GDPR and Data Governance: A hand in hand affair

The introduction of GDPR should not be seen as a burden for companies but rather as an opportunity to review all the data governance policies that are in place. Companies should be able to find the right balance between GDPR and their data governance structure.

Companies could create a competitive edge by not only addressing how they manage the personal data but for all the data they hold. If companies get it right, they could discover new business opportunities waiting to be exploited.

As we all know by now, the GDPR gives every EU citizen the right to know and decide how their personal data is being used, stored, protected, transferred and deleted.

Those companies that put data privacy at the forefront of their business strategy would be the ones who are clearly and efficiently managing their customer data in a fair and transparent way. Hence giving them the competitive edge based on privacy.

One of the requirements of GDPR is to document what personal data is held, where it came from and who is it shared with. By really understanding the data they hold, companies could be made aware of the data they can gather, as well as analyse and apply this data to boost sales or marketing efforts.

Companies should ensure that their data governance structure will support the GDPR requirements. Policies and procedures need to be created or re-assessed to help keep corporate data consistent and ensure that it meets the information needs of business users. It is also an opportunity to review data management practices.

The GDPR requirements combined with a robust data governance structure could give organisations the opportunity to become a data-driven company based on building tools, abilities, and a culture that acts on data hence really making an internal transformation around data.

Data Regulations
10 septembre 20180

20 Fun Facts about GDPR ?

  1. GDPR is short for General Data Protection Regulation.
  2. GDPR are rules for the protection of personal data inside and outside the EU.
  3. The aim of GDPR is to give residents control over their personal data and unify the regulations within the whole Union.
  4. GDPR went into effect on May 25 ,2018.
  5. Seven key guiding principles to process personal data.
  6. GDPR covers aspects of data security, rights and freedoms of EU data subjects, regulatory compliance and risks, data governance and control of data.
  7. GDPR is enforced by the supervisory authority in each member state.
  8. GDPR affects any and every organization across the world that does business with people in EU member states.
  9. It makes organizations directly accountable for what they do and don’t do with sensitive EU citizen data. This also includes governments agencies and other public associations.
  10. There are a lot of processes and procedures to document!!
  11. Technology plays a very important role.
  12. GDPR allows for a 360 degree view of data subjects and a single source of truth.
  13. Certain organisations that process data may be required to appoint a Data Privacy Officer.
  14. The GDPR imposes a set of serious penalties on data controllers and processors for non-compliance.
  15. The GDPR maximum penalty is 4% of global annual turnover or €20 million – whichever is higher.
  16. A written warning can be sent to organisations in cases of first and non-intentional non-compliance.
  17. Fines under GDPR of up to 10€ million or 2% of annual worldwide turnover will be imposed on organisations that don’t uphold the obligations of data controllers.
  18. If an organisation incurs a data breach, they should notify the relevant authorities within 72 hours.
  19. Implementing the GDPR is not an option, but a legal requirement, which needs a high degree of commitment and resources.
  20. GDPR can offer numerous opportunities with a well-designed internal data protection framework.
Data Governance
06 septembre 20180

How does your data appetite look like ?

Digital capabilities are changing fast, making it hard to know whether you are ahead of the curve or falling behind. A digital transformation isn’t complete unless a business adopts big data.

Are you already on the bandwagon or are you not sure where to start? If you can answer the following questions then you are on a roll!! If not there’s still time to make a difference.

1)     Are you overwhelmed by the data that is flooding in at great speed and in high volumes?

2)     How much is your data worth?

3)     Do you know how data was created in the past and how it is created now in your organisation?

4)     Do you use data to create strategic opportunities?

5)     Are your analytics aligned with the overall organization’s strategy?

6)     Is your IT dept ready to support the rapid development and implementation of new digital marketing capabilities?

7)     Who carries the bat for digital transformation in your organisation?

8)     Can you analyse big data quickly and make fact-based decisions?

9)     Are you capturing, sharing and managing corporate data assets?

10)  Can you learn more than has ever been possible about what your customers want?

Self-service Analytics
29 août 20180

Leveraging data to grow your business

As an HR leader, you need an overview of the different aspects of your company’s biggest asset: your employees. Having an authentic view of the state of your workplace specificities and needs, your workforce planning, is not an easy task.

HR data are disseminated across various systems; Business Lab helps you combine them all and visualize the impact of retention initiatives on employee productivity, or their overall satisfaction. Measure your workforce value with modern HR analytics and drive business performance with interactive dashboards.

Gather and manage all this data in one place while allowing other people to work on it and keep a unique version of the truth in any case.

We are always happy to talk with potential and existing customers! Please get in touch if you desire more information about our company or products and services.