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Big Data Solutions for Business

The Need For Big Data Solutions

Today’s organizations face an explosion of data from more sources than ever before. As a result, many companies are rethinking their approach to traditional enterprise storage and architecture to leverage big data. Storing and managing these huge pools of information is a challenge for many enterprises, but big data also offers significant opportunities.

To achieve these benefits, companies must process data big data to create value that can help drive better decisions. And by processing big data in real time, companies can engage powerful analytic strategies to take advantage of market shifts and stay ahead of competitors.

At GoodWorkLabs, we take the strategic advantage of Big Data and assist companies in making the most of their resources.

What is Big Data?

Big data describes a holistic information management strategy that includes and integrates many new types of data and data management alongside traditional data.

Big data has also been defined by the four Vs:

  • Volume. The amount of data. While volume indicates more data, it is the granular nature of the data that is unique. Big data requires processing high volumes of low-density, unstructured Hadoop data—that is, data of unknown value, such as Twitter data feeds, click streams on a web page and a mobile app, network traffic, sensor-enabled equipment capturing data at the speed of light, and many more. It is the task of big data to convert such Hadoop data into valuable information. For some organizations, this might be tens of terabytes, for others it may be hundreds of petabytes.

  • Velocity. The fast rate at which data is received and perhaps acted upon. The highest velocity data normally streams directly into memory versus being written to disk. Some Internet of Things (IoT) applications have health and safety ramifications that require real-time evaluation and action. Other internet-enabled smart products operate in real time or near real time. For example, consumer e Commerce applications seek to combine mobile device location and personal preferences to make time-sensitive marketing offers. Operationally, mobile application experiences have large user populations, increased network traffic, and the expectation for immediate response.

  • Variety. New unstructured data types. Unstructured and semi-structured data types, such as text, audio, and video require additional processing to both derive meaning and the supporting metadata. Once understood, unstructured data has many of the same requirements as structured data, such as summarization, lineage, audita-bility, and privacy. Further complexity arises when data from a known source changes without notice. Frequent or real-time schema changes are an enormous burden for both transaction and analytical environments.

  • Value. Data has intrinsic value—but it must be discovered. There are a range of quantitative and investigative techniques to derive value from data—from discovering a consumer preference or sentiment, to making a relevant offer by location, or for identifying a piece of equipment that is about to fail. The technological breakthrough is that the cost of data storage and compute has exponentially decreased, thus providing an abundance of data from which statistical analysis on the entire dataset versus previously only sample. The technological breakthrough makes much more accurate and precise decisions possible. However, finding value also requires new discovery processes involving clever and insightful analysts, business users, and executives. The real big data challenge is a human one, which is learning to ask the right questions, recognizing patterns, making informed assumptions, and predicting behavior.

 

The GoodWorkLabs Advantage

Under our able supervision, Big Data can change your business fortunes. It can do wonders to your analytics and information gathering. It has the following advantages.

  • Big Data is Timely – 60% of each workday, knowledge workers spend attempting to find and manage data.

  • Big Data is Accessible – Half of senior executives report that accessing the right data is difficult.

  • Big Data is Holistic – Information is currently kept in silos within the organization. Marketing data, for example, might be found in web analytics, mobile analytics, social analytics, CRMs, A/B Testing tools, email marketing systems and so on.

  • Big Data is Trustworthy – 29% of companies measure the monetary cost of poor data quality. Things as simple as monitoring multiple systems for customer contact information updates can save millions of dollars.

  • Big Data is Relevant – 43% of companies are dissatisfied with their tools ability to filter out irrelevant data. Something as simple as filtering customers from your web analytics can provide a ton of insight into your acquisition efforts.

  • Big Data is Secure – The average data security breach costs $214 per customer. The secure infrastructures being built by big data hosting and technology partners can save the average company 1.6% of annual revenues.

  • Big Data is Authoritative – 80% of organizations struggle with multiple versions of the truth depending on the source of their data. By combining multiple, vetted sources, more companies can produce highly accurate intelligence sources.

  • Big Data is Actionable – Outdated or bad data results in 46% of companies making bad decisions that can cost billions.

 

Contact our Big Data experts today and set the ball rolling towards a future with better data interpretation and usage.

You will not be disappointed.

Contact Us

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